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Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

By Felipe Flores
Artificial intelligence is a tremendously beneficial technology that's advancing at an incredibly rapid pace.
As more and more organisations adopt and implement AI we find that the main challenges are not in the technology itself but in the human side, ie: the approaches, chosen problems and what's called 'the last mile', etc.

That's why Data Futurology focuses on the leadership side of AI and how to get the most value from it.

Join me, Felipe Flores, a Data Science executive with almost 20 years of experience in the space. Every week I speak with top industry leaders from around the world
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SL-3 #RealTalk: The Covid19 Juggle- Women in TECH Talk About the Challenges of Working from Home
When lockdowns started, people around the world, especially women, found themselves juggling with their personal and professional lives. In this episode we have Kathryn Gulifa, Chief Data & Analytics Officer at Worksafe Victoria, and Stuti Sharma, Director of Data Science at Visa who share with us the challenges they faced while trying to cope with the new normal. Stuart Garland, Director at Talent Insights Group gives us the recruiters’ perspective on the covid impact and tells us employees are not the only ones adapting to changes, employers are doing so as well. Some of them are beginning to realise remote work can be productive and perhaps there is an opportunity for some work from home to offer employees flexibility post covid-19. Quotes: "I was trying to balance full time work while caring for a 2 year old and a 6 month old. Which I found, honestly, really challenging and had many ups and downs from the mental health perspective, both trying to understand my place in the world having just returned from work and joining back into an organization that was facing a very different economic situation and different priorities than when I left." "I had my laptop setup on the dining table and it was always there, even over the weekends. I think it was mostly self-inflicted, I would find myself working late in the night and then I realized that it was not sustainable. This thing was not ending anytime soon, and I made a conscious effort to draw a line between my office hours and time with my family." "I have a team member that says it’s not working from home, it’s living at work." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 3 Enjoy the third episode of our #SheLeads Series!
47:40
October 20, 2020
SL-2 How the Pandemic Highlighted the Need for Data-Driven and Diverse Leadership
Anu Madgavkar is a partner at McKinsey Global Institute and she’s done important research on Covid-19’s effect on gender inequality and the future of women at work. Anu talks about the diversity dividend and the compelling statistics supporting it. A study from +1000 companies around the world, found that organizations in the top quartile in terms of diversity in C-suite executives are 25% more likely to outperform in terms of profitability and long-term value creation. This holds true for gender and ethnic diversity. Also, companies in the bottom quartile are 29%  more likely to underperform, resulting in lower profitability or average value creation. Quotes: "I started focusing more on this notion that there’s a really leaky pipeline and a lot of women do dropout, and as you start thinking about that and navigating your own journey through that I think I got a lot more interested in why does this matter to the world at large, to economies and to women around the world." "Looking out 10 years I would say that the pace at which automation is changing the inherent work that we are all doing, that is going to accelerate and that is going to affect all people in the workforce." "Both automation as well as the trend towards more alternative work arrangements will both likely accelerate post-covid." "It’s a period of great innovation and experimentation and I think we really need to embrace this time to be more aggressive and experiment with more gender-friendly ways of support, both on the government policies side as well as the business side." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 2 Enjoy the second episode of our #SheLeads Series!
49:20
October 13, 2020
SL-1 Championing Diversity
Data Futurology podcast host, Felipe Flores interviews She Loves Data co-founders Jana Marlé-Zizková and Pavel Bulowski, who share how they found a philanthropic niche in data literacy while pushing for more diverse and inclusive workforces. What started as a data workshop for a roomful of friends and friends of friends, has grown into a 21k+ community in 14 (and growing) city chapters around the world. Listen to inspiring stories from them and their members. Jana and Pavel both have abundant experience in the analytics field and also co-founded Meiro, a Customer Data Platform that allows organizations to harness user data. Jana was recently recognized as part of Singapore’s 100 Women in Tech. More than just a non-profit, She Loves Data is a community and a movement with the goal of encouraging women across Asia, ANZ, Africa, Europe and the USA to embrace tech and strengthen their data and digital literacy to future-proof their careers. Quotes: "There are only like 25% of women in this field. How about going out there and inspiring women to look at data as a possible future career." "You are changing people’s complete life trajectory by lowering the barriers to entry into something that they can find their passion and interest in." "It’s never late to change your career, it’s never late to learn about tech and data because it can help you for your future career, your jobs and maybe make your life more meaningful." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: https://www.sheleads-datafuturology.com/episodes/event-one-bkj8b Enjoy the first episode in our #SheLeads Series!
1:02:25
October 6, 2020
#136 Putting AI to Work: Delivering Actionable Insights with Machine Learning and Deep Learning with Dr. Alex Antic
Dr. Alex Antic is the Head of Data Science at the Software Innovation Institute. He has 17+ years of experience across different industries including Federal and State government, Insurance, Asset Management, Banking (Investment and Retail), Consulting and Academia. Alex has recently been recognised as one of the Top 10 Analytics Leaders in Australia by IAPA (Institute of Analytics Professionals of Australia). He describes the early days of his career as a time for personal growth and honing in his technical skills. Now, his goal is to use data science and artificial intelligence for public good, and as a way to drive impact and change. Alex is an enthusiast of the experimentation culture; he believes in the fail fast and fail cheap notion and how it is important for organizations to not be scared of failure, given that this can keep them from moving towards innovation. Quotes: "Can’t take out the human element when it comes to analytics. Analytics only gets you so far, you have to think about broader applications." "People need to think about what problem they are solving and if it needs to be solved by a complex method." "When you are trying to solve a problem, start with the simple solution first, and add complexity as you need to, as sometimes the non sexy elements will add value to the organisation, such as automating an excel file .. You don’t often or always need to go down the complex deep learning algorithm to extract value, as it will make it difficult to explain and difficult to validate, and simplistic is beautiful in many ways." Read the full episode summary here: Episode #136 Enjoy the show!
57:33
September 21, 2020
#135 How AI is Transforming Retail with Khalifeh Al Jadda - Director of Data Science
We have Khalifeh Al Jadda, Director of Data Science at Home Depot. Khalifeh has solid knowledge in large scale machine learning and data mining techniques. He tells us how in retail some businesses are still running manually, without the use of automation tools, so the job of data science leaders is to educate business partners and show them by example and with data the value that data science and artificial intelligence can deliver to their organizations. Later on, he explains their workflow is managed by product managers and starts with the data scientist taking the responsibility of building the machine learning model, training the model, validating it and even going all the way towards testing it. Then, machine learning engineers take over and scale up the code, they clean it, perform unit testing and do everything needed for it to be ready for production. Quotes: "I started my journey in the industry from that point, which was the first internship I got in 2015. That’s the first advice I give to anyone, if you are in graduate school, if you are a student, make sure to pursue an internship before graduation. It’ll make your life much easier after graduation." "It’s been an interesting journey, a great journey. I hope that everyone actually goes through those challenges in their careers, because  it makes you a better and stronger data scientist." "You cannot build a team with only computer vision people, or a team with just statistical people. You need to bring people from different backgrounds. That’s what my organization includes. It includes people from all backgrounds." Read the full episode summary here: Episode #135 Enjoy the show!
56:19
September 15, 2020
#134 Empowering Virginians with Trusted Data with Carlos Rivero - Chief Data Officer
In the 6th episode of our “Bitesize Insights for Data Driven Leaders” Series, we have Carlos Rivero, Chief Data Officer at Commonwealth of Virginia. Carlos started college wanting to become a civil engineer to help with his father’s business, but later on gravitated towards environmental engineering and ecology given that he lived in Miami and was a witness to the environmental impact on their local marine ecology. Thanks to the advice of one of his professors and mentor, he chose science over engineering. For Carlos, it’s very important to bring people together and have them understand the value of the work they are doing, why they’re doing it and the impact it can have on real world issues. Quotes: "Take money out of the equation and simply focus on what brings you fulfillment and happiness." "It became clear to me that I loved working with data and being able to tell stories from those data assets that I was working with." "One of the basic things that I really enjoyed about those projects was being of service, because it was not just geographic information science that I was working on, it was really at the service of something larger than that, of something that had potential impact in our social sphere and that to me was extraordinarily appealing and that was a big driver for the impact these projects had on my career." Read the full episode summary here: Episode #134 Enjoy Carlos Rivero in our “Bitesize Insights for Data Driven Leaders” Series!
27:32
September 7, 2020
#133 Importance of Data Translators & Data Foundations: Investing in the 'Golden Record' with Elisa Koch - Head of Data and Analytics
In the 5th episode of our “Bitesize Insights for Data Driven Leaders” Series, we have our first ever live audience episode with Elisa Koch. She is the Head of Data and Analytics at the AFL - Australian Football League. Elisa spent 10 years working for Avon Cosmetics, mostly in Latin America. That’s where she had her first encounter with marketing analytics and she fell in love with data once she discovered the link it has with customer behavior. Elisa shares her take on data translators and how she considers they are the first people you need to hire. Several organizations are not savvy enough to know how to apply their data and that’s why they need data translators to make their data approachable. Stay tuned to learn more about Elisa and the work she is doing at the AFL towards merging the sports analytics and marketing data worlds together to better understand their fans and grow their audiences. Quotes: "When I figured out that you can use data to try to predict what will happen in the future, that blew my mind." "Ask questions, be curious, do your research and figure it out." "A lot of organizations are not savvy enough to know exactly how to apply data and are even scared of it. The beauty of data translators is they make data approachable." Read the full episode summary here: Episode #133 Enjoy Elisa Koch in our “Bitesize Insights for Data Driven Leaders” Series!
34:10
August 18, 2020
#132 Data For Good, with Chief Data Officer of the City of LA, Jeanne Holm
In episode 4 of our “Bitesize Insights for Data-Driven Leaders” Series, Jeanne Holm is the Chief Data Officer at her hometown, the City of Los Angeles. She works at the cross-section of civic innovation, open data, and education, addressing issues ranging from homelessness to digital equity technology innovation, data and analytics, and public-private partnerships. As CDO, Jeanne focuses on taking data, like the number of people trained in the city’s workforce centers or how sustainable their practices are, and making it available and accessible to the taxpayers. To enable this, she works with individuals within the government that are not data scientists, and provides support and data literacy training in order to facilitate their understanding on  how to structure, manage and put context around data. She also cooperates with entities outside the government, like academic researchers, businesses, and advocacy groups who want to use the data but need the information and context around it. Quotes: "The thing that connects all of these different pieces is wanting to tell stories that help people create different actions." "A Chief Data Officer focuses on organising and helping to bring out the data from different parts of the organisation and then either to make it easier to share within the organisation or to also share that out with the public." "If you set the directions, set the pace, and support people and are compassionate to their own issues; I think you can build and lead an amazing group of people." Read the full episode summary here: Episode #132 Enjoy Jeanne Holm in our “Bitesize Insights for Data-Driven Leaders” Series!
30:51
August 10, 2020
#131 AI & Technology, Key Drivers for Scaling and Optimising the Value Chain with Steve Monaghan – EVP, Chief Digital Officer
Steve Monaghan is the Chief Digital Officer at Riyad Bank. He has a series of investments in banking and insurance using AI and new technologies in order to improve efficiency. He started out as a commercial pilot working 22 hours a day, running the aviation company during the day and flying at night. His first contact with data came when he started using spreadsheets to automate tasks and accelerate the time in which he got them done. His career then moved from flying into technology. For Steve, the three core laws of technology that drive data science and AI are: Moore's Law: processing power doubles every 18 months for the same cost. Metcalfe's Law: the value of a network grows by the square of the network's size. Kryder's Law: storage doubles every 13 months for the same cost. He believes these 3 laws encompass the ability you have to assimilate learning into knowledge. Quotes: “What technology does is, it arbitrages time, and you get to live in someone else’s future, which is the most powerful proposition on the planet, and especially what data science enables one to do, is to achieve this at scale.” “One of the main problems in data science and analytics is the adoption of the work, the last mile and being able to have the impact that technology promised.” “It is all logical, and it is all there , so work it out. Technology and data science is logical, it's only about putting our mindset and attitude towards it and working it out. Because everything we do in the tech space is driven by some level of logic, and if its logical it can be done. Don’t accept your own limitation find a way to work around it.” Read the full episode summary here: Episode #131 Enjoy the show!
59:51
August 3, 2020
#130 AI, Ethics and the World of Health Data with Christopher Boone – Global Head of Health Economics & Outcomes Research
Christopher is the Global Head of Health Economics & Outcomes Research at Abbvie, an adjunct professor at NYU Graduate School of Public Service and active board member of several influential organizations. He has received numerous recognitions in the past. In 2019 he was named a Top 100 Innovator in Data Analytics, in 2018 an Emerging Pharma Leader and in 2017 he was a Top 40 Under 40 in Minority Health Honoree by the National Minority Quality Forum Christopher explains how, in his eyes, all human data is healthcare data, and how excited he is at the applications this data might have if we learned how to analyze it in a better way, given that, currently, only 5% of all the available data is being analyzed.  Stay tuned to know how the broad array of experiences he had in organizations like non profits, government and pharmaceuticals helped him learn to think outside the box and gain a broader perspective. Quotes: "I'm just not feeling it, it's just not meaningful to me and I just want to help people. "In my eyes, all data is healthcare data." "I think that the problem that we have is we're still in a society where there's fear of the unknown and I also think that in some cases the system is set up to benefit folks from having a level of fragmentation even lack of data quality." "You also have to identify what is the benefit or value proposition for each of these individuals or groups within the organisation for them to really buy into it." Read the full episode summary here: Episode #130 Enjoy Christopher Boone in our “Bitesize Insights for Data-Driven Leaders” Series!
31:22
July 27, 2020
#129 Entrepreneurship Tips from Australian Shark, Steve Baxter – Partner & Investor
Steve is an investor, a partner at TEN13, and you may also know him as one of the sharks from the show Shark Tank in Australia. His journey in entrepreneurship and investments began over 25 years ago when he started his first company in the telecommunications area. He sold his second business in 2010 and went on to become an investor. Currently, he has an existing portfolio of over 30 companies. He was Queensland Chief Entrepreneur for three years, he does mentorships and is also a qualified pilot. Steve has several investments in the US and he draws a comparison between the start-up scene there and in Australia. Stay tuned as Steve shares his life experience and provides both tips and inspiration for anyone thinking of starting their own business or already working in their start-up. Quotes: “Really bad investments are easy to find… if you can sell to your customers it is a far easier way forward.” “If you're doing it and you know it's wrong, stop it and do anything else.” “The thing about bad news is when you hide it, it just doesn't get any better.” “You're either shooting the lights out or shooting your brains out” Thanks to our sponsor: We are Rubix. Read the full episode summary here: Episode #129 Enjoy the show!
1:03:15
July 21, 2020
Data Futurology Español Ep #1 with Day Manuet
Felipe Flores es director de data science con casi 20 años de experiencia. Felipe ha trabajado en ingeniería de datos / almacenamiento, reportes, inteligencia empresarial, análisis, data science, machine learning e inteligencia artificial. Actualmente es el Director de Data Science en la empresa de Inteligencia Artificial, Honeysuckle Health. Mientras que Day es una experta en data science. Durante 15 años, ha colaborado con corporativos internacionales como Colgate, Gillette, P&G, Walmart y Epworth HealthCare para guiar su estrategia de inteligencia empresarial, de mercadotecnia y decisiones operativas mediante el uso de datos. Le apasiona todo lo que tenga que ver con datos e insights, es experta en técnicas cuantitativas, cualitativas y analíticas y ha trabajado con bases de datos, inteligencia de mercados, reportes de datos, ciencia de datos, pronóstico de ventas para innovaciones, machine learning e inteligencia artificial. En este episodio Felipe y Day nos dan una breve pero integral introducción a que es Data Science. Platican de cómo desarrollar las capacidades de data science en una empresa y la importancia de la cultura para implementar proyectos de datos exitosos. También nos dan tips de como empezar a desarrollar tu Carrera en Data Science entre otros temas fundamentales de Data Science. Temas: [03:20] ¿Qué es Data Futurology y ¿cuál es su objetivo? [07:30] Trayectoria de Felipe Flores [16:30] ¿Qué es Data Science/Ciencia de Datos? [19:45] Tips para desarrollar las capacidades de Data Science en una empresa [24:10] Sugerencias para alguien que empieza su carrera en data science [27:20] Como mantenerse al día en el mundo de data science dado el avance de la tecnología [32:30] Cómo especializarse en data science si mi carrera no está relacionada en data science [34:10] Entendiendo las diferencias de inteligencia artificial, machine learning, deep learning y data science [43:10] Cómo interactúa la Mercadotecnia con Data Science [44:35] El rol de la cultura en una organización para implementar data science [48:00] Tipos de algoritmos [53:50] ¿Qué es la minería de datos? [55:30] Libros recomendados para Data Science Frases: “La idea de un científico de datos es poder mejorar el desempeño de una empresa ocupando datos”. “Data science no es una caja de pandora sino hay una explicación detrás de cada algoritmo”. “El error más común es que la gente espera terminar el proyecto y decirle a un área que le va hacer el trabajo mucho mejor; la gente que tiene que generar el cambio deben colaborar con la gente de data science desde el principio de un proyecto”. “Nadie puede mantenerse al tanto de todo lo que está pasando en data science; es importante entender lo fundamentales de machine learning y estadística y con eso cualquier desarrollo que se de en cualquier área y así cuando necesitas aprende en cualquier área”. “En general el conocimiento depende de la persona cuando uno se quiere exigir y esforzarse; el conocimiento existe lo más importante es practicar poner los conocimientos en práctica”. “Uno puede tener los planes más espectaculares, pero si la cultura no existe nada va a funcionar; la cultura es el ingrediente más importante de data science”. Join Data Futurology on Telegram: https://t.me/datafuturology Únete a Data Futurology Español en Telegram: https://t.me/df_espanol YouTube: https://www.youtube.com/watch?v=WRop1cfFVo8&t=135s 
1:04:51
July 18, 2020
#127 Reinventing Prostate Cancer Testing with AI: From Development to Regulation to Production with Elliot Smith – CEO & Founder
Elliot Smith is the CEO and founder of Maxwell Plus. A visionary company that has been using machine learning and artificial intelligence to help treat and diagnose patients with prostate cancer. The way they bring in the data, help analyze it and help people along their journey is fascinating and makes them leaders in this specific field. Elliot is very passionate about helping others find diseases at a point where they can be treated. To know where things are, if they should be treated and how best to treat them is his ultimate goal in terms of applying data science and AI to the medical world. Stay tuned to know how his desire to build something that could be useful in the real world turned into a company with the potential of impacting the lives of over 300 million men that have or are being diagnosed with prostate cancer. Quotes: When I finished that I sort of came to the realisation that I loved academia, but it was a little bit too slow moving for me. I wanted to be out there building things, putting stuff out into the world and decided to have another run at building a start-up and at the time I happened to know a lot about numerical modelling, optimisation and how that translated into things like AI and also medical imaging and without jumping too far ahead that's the point where all of this came together and the company that I now run Maxwell plus was born in that collision of worlds. We looked at their data, we saw something in their data that wouldn't have been picked up otherwise and our doctors said we need to act and with the hindsight of knowing their outcomes we acted at the right time and those people have what is for prostate cancer is 98% 5 year survival rate because we acted in time to avoid that conversation. If you have had treatment or you choose to go into what is called active surveillance, which is let’s just watch this and determine when to treat, the algorithm that we apply to do initial diagnosis apply just as well to monitoring your diagnosis over time. How can we then go to provide ongoing support to really see these men through from day one to day infinity and continue to provide real clinical value to these men. Read the full episode summary here: Episode #127 Enjoy the show!
1:01:03
July 13, 2020
#126 Data-Driven Approaches From Politics to Aerospace with Adam Bonnifield – VP Artificial Intelligence
In episode 2 of our “Bitesize Insights for Data Driven Leaders” Series, Adam Bonnifield is a VP of Artificial Intelligence at Airbus. He is a former Chief Product Officer (Census) at the U.S. Department of Commerce and Co-Founder of Spinnakr and Giv.to. Adam lives and breathes online engagement - he ran digital strategy for political campaigns since he was in college, breaking Congressional fundraising records. After graduating from Cambridge University, he was awarded the Tsuzuki Fellowship to direct online youth outreach in Japan. Enjoy Adam Bonnifield in our Bitesize Insights for Data Driven Leaders” Series! Quotes: “Don’t talk so much when you’re the boss. Just stop talking so much about stuff.” “You have a sort of natural optimism because you have the experience of building something from nothing. And realizing that anything can be done, especially in data technology. At the same time, you’re a child when it comes to navigating corporate politics. “I was the kid that went to the Aerospace Museum every week. I am in love with aircraft. When you work with a company with a specialized product, you’re surrounded by people with a patriotic feeling for what they do.” “It was a special time because it wasn't really known what you could do with data.” “If you're working in data science, I would look for companies with complex supply problems." “We need a new paradigm of data storytelling and data visualisation built for regular people.” Read the full episode summary here: Episode #126 Enjoy the show!
41:05
July 9, 2020
#125 Transitioning From Academia to Business – The Skills Gap with David Hardoon – Senior Adviser for Data and Artificial Intelligence
David is the Senior Advisor for Data and Artificial Intelligence at UnionBank Philippines. Concurrently David is an external advisor to Singapore's Corrupt Investigation Practices Bureau (CPIB) in the capacity of Senior Advisor (Artificial Intelligence) and to Singapore's Central Provident Fund Board (CPF) in the capacity of Senior Advisor (Data Science). David loves the idea of programming logic. We have the ability to use information as mechanisms to assist us on a day-to-day basis. So, David was inspired to explore the possibilities of data. After high school, David considered artificial intelligence or astrophysics. However, he ended up finding a place that has a combined degree of computer science and artificial intelligence. In fact, he was the second student to complete the degree. Stay tuned as David gives his perspective on data governance – it's a mechanism that allows us to identify what we should and shouldn't do. In addition, David reveals his views on AI governance, and David explains how he balances all of his work. Quotes: “I was called a geek many, many times in my life, so I’m going to own it now.” “The objective is: how do you take these very complex ideas, and explain them in very pragmatic, very relatable terms.” “I personally have a bit of an aversion to the term [data scientist], for two reasons: every scientist uses data, and it’s just too generic.” “We need to also equally realise when data isn’t relevant, … a process is what’s required.” Read the full episode summary here: Episode #125 Enjoy the show!
54:42
July 6, 2020
#124 The Data Science Team: Skills Needed, Purpose and How to Structure with Dan Costanza – Chief Data Scientist
Dan Costanza, Chief Data Scientist at Citi, joins me for the first episode in the new “Bitesize Insights for Data Driven Leaders” Series. Dan opens the show by explaining how he got interested in data. After graduating from college, Dan went into an investment banking role. Eventually, he received an exciting project that got him started down the data path. Dan says as someone who didn’t study computer science in school, it has been a heavy lift trying to get those technical skills up to par. During a code-heavy project, Dan needed to learn how to break up the project and work through it. Also, he learned how to think about sampling data without bias. Then, Dan explains the importance of emotional intelligence for data science. Conscientiousness and emotional intelligence are the things that you can actually interview for. Instead of judging people on their grades, we need to judge people on their ethics, communication skills, and willingness to work in teams. In India, Dan set up a data science team. The talent in India is insane. However, there are cultural differences Dan needed to work through. For instance, he told his team that they needed to speak up when they had ideas. If you create space for people to bring their own thoughts, you’ll hear loads of good suggestions. Before Dan told his team that, they would withhold useful information. Quotes: “When you look at the hiring research again, like there are two real categories and the one is things you don’t interview for, which are the intellectual horsepower things and those are - how smart you are, do you have some specific skills I need. The word that always comes up on the other side is conscientiousness, and that encompasses the stuff we talked about at the beginning, and the emotional intelligence, teamwork parts of it and those are the things you do actually interview for. Which is counterintuitive for a lot of people who work in quanti type roles because you want to ask people really hard questions, to see if they are smart, but the problem is the data doesn’t support that as being predictive of anything when you control for their grades.” “You start by spraying things around, working with a lot of people, just to get the volume in and see who those people are and meet people, and as you work a little bit, you start to understand their own types of workflow.” “More powerful then compliant is having good ethics there on the ground.” Read the full episode summary here: Episode #124 Enjoy the show!
30:12
July 3, 2020
#123 Why We Need to Focus on Implementing Data Governance with Michelle Pinheiro – Head of Enterprise Data Governance
Michelle is Head of Enterprise Data Governance at ANZ Bank. In this role, Michelle is responsible for Data Governance strategy across the group, ANZ Data Privacy and Ethics framework, Enterprise Metadata Management, Data Risk and a Centre of Excellence for Data Quality. Michelle has over 25 years of experience in the world of Data and utilizes that knowledge to help foster organized and sustainable large scale analytical environments for commercial success. Michelle has a particular interest in building frameworks for ethical data use by successfully developing ANZ’s principles for Data Ethics. In this episode, Michelle describes the importance of transparency in data ethics. For instance, in the world of insurance, people want to know how their premium is calculated. What information is the company using to calculate the insurance premiums? So, the insurance company needs to explain what information they are putting into the black box. Insurance algorithms for premiums are like the formula for Coca-Cola; no one ever shares it. To combat this, Michelle needed to put herself in the mindset of the customer. Stay tuned as Michelle explains how the customer journey can benefit from data governance. Also, Michelle reveals where she thinks the future of data ethics is going, how data ethics overlaps with data governance, and the ways that consent fits into data ethics. Quotes: “I did a lot of work in redesigning documents and determining what information to disclose and that really comes down to transparency and transparency is a big aspect of data ethics.” “That was a legislation where you actually had to articulate what are the factors, what is the information that you give us that we actually then use to calculate your premium. So it took it from being an enigma to explaining these are the inputs that we put in. And that's got a lot of relevance to today's world with artificial intelligence which is what information are you putting into that black box to then produce the outcomes that are going to impact me. And so I guess that's the genesis of it and that was a really big change in the insurance world because insurance algorithms for premiums are like the formula for Coca-Cola nobody ever shares them anywhere.” “I'm not shy about saying you know data is not part of the IT world, it's part of the business world.” Read the full episode summary here: Episode #123 Enjoy the show!
1:01:03
June 30, 2020
#122 Optimising Conversational AI Dialogue Systems with Dr. Maria Aretoulaki - CEO
DialogCONNECTION was founded in 2008 by our Director and Lead Consultant, Dr. Maria Aretoulaki. Maria has been designing Speech IVRs and Voice User Interfaces (VUIs) since 1996, long before Voice Assistants, but also before telephone self-service was mainstream. She got into Voice through a Post-Doc in Spoken Dialogue Management for Speech recognition applications, after having got a PhD and an MSc in NLP and Machine Learning and a BA (Hons) in Linguistics & English. In this episode, Dr. Maria explains how she started in the data space. When looking through the list of available master's degrees, she found one in machine translation and was utterly fascinated. Dr. Maria learned how to translate Spanish sentences into English sentences using machine translation. There are all sorts of rules and contexts that the machine needs to learn. For instance, because language is complex, it's difficult for a machine to pick out which sentences belong in the summary of an article. Humans can't even all agree on which sentences belong in a summary! Quotes: “[To start your own company] You're never that prepared.” “Usually we were approaching people to do a project, but rarely would "go live" materialise.” “Flexibility, multitasking and resilience are the main lessons.” “How you formulate a question is really important.” “But also you get an insight into things you haven't even thought about.” “Every single connection is valuable” Read the full episode summary here: Episode #122 Enjoy the show!
1:08:10
June 25, 2020
#121 The Strategic Importance of Data Warehousing and Analytical Software With Craig Rowlands – Senior Executive Information Management
Craig Rowlands is the Senior Executive Information Management at Medibank. Craig’s role is to provide thought leadership, aligned with expertise in delivering pragmatic business focus information management solutions whilst leading improvements in the data landscape. Whilst at Medibank, Craig has transitioned Medibank from a legacy data management team to a cloud first data capability based on a DevOps methodology to provide Medibank with the right technology, process and people to achieve its long term aspirational objectives. He has an extensive background in data, commencing in the UK until he moved to Australia in 2011. Whilst in the UK Craig worked for blue chip banking and finance industry leaders such as Barclays, First Direct, GE and Hbos. His first role in Australia was with ANZ as Head of Decision Systems. Craig joined Medibank from Latitude Financial Services (formally GE) where as Head of Data Management he led a large team responsible for data strategy & design, data governance and business intelligence reporting. Quotes: "You reach a crossroad in your career as an analysts where you either stay true to yourself and be a technician or you move into a leadership position role where you bring others along the journey." "There is so much variety in data today. From the data science world to the reporting world to the information management world and all the roles in there. To become a good leader, my view was I needed to know at least a little bit about each area." "[Helping the customer] is the outcome and the power that data can provide." "So, my philosophy has always been I give them 2 or 3 small wins backed up by 1 big one. We keep the momentum going because that way we can keep the seed funding going." Read the full episode summary here: Episode #121  Enjoy the show! 
1:00:18
June 23, 2020
#120 Natural Language Processing with Catherine Havasi – CEO
Catherine Havasi's dream and mission are to give computers the ability to think about the world more like a person and less like a machine. Equally important is putting this innovation into practice in a way that effects real business outcomes and transforms our everyday lives. Catherine has twenty years of experience in directing and doing cutting edge research, operationalizing it, and using it to drive real results. In this episode, Catherine explains how she started in the data world. Read this full episode summary on our website: #120 Natural Language Processing with Catherine Havasi – CEO Enjoy the show!
42:11
June 19, 2020
#119 Finding Success in Data-Driven Entrepreneurship with Dr. AnnMaria De Mars – President
Dr. AnnMaria has a proven track record in founding successful businesses. 7 Generation Games is her fourth company and a spin-off of her consulting firm, The Julia Group. She was previously the president of R&R Consulting and Vice President of Spirit Lake Consulting, Inc. and is also currently CEO of the Julia Group. Both the Julia Group and Spirit Lake Consulting went on to generate over $1 million in contracts. She has authored grants that have received tens of millions of dollars in funding, including more than $30 million for Native American programs. Read this full episode summary on our website: #119 Finding Success in Data-Driven Entrepreneurship with Dr. AnnMaria De Mars – President Enjoy the show!
48:02
June 16, 2020
#118 Smart Tech Meets a Smart Dr’s Passion to Solve Blindness with Andrew Bastawrous – Co-Founder & CEO
#1 in our new Innovation and Entrepreneurship Series, Andrew is an Ophthalmologist (Eye Surgeon) and Associate Professor in International Eye Health at the London School of Hygiene & Tropical Medicine. He has worked and researched in over twenty countries, including two years living in Kenya, where he led a significant eye disease study and the development and testing of Peek. In this episode, Andrew reveals his own story and how he found out about his poor vision. When Andrew got glasses, his life completely changed. Read this full episode summary on our website: Smart Tech Meets a Smart Dr’s Passion to Solve Blindness with Andrew Bastawrous  – Co-Founder & CEO Enjoy the show!
40:51
June 12, 2020
#117 Driving commercial opportunities at F1 with Max Métral – Senior Analytics Manager
Max Métral is a self-motivated professional with a successful track record in data science and analytics cross-functional roles for worldwide organizations. In this episode, Max dives deep into his background and how he found his interest in data. Read this full episode summary on our website: #117 Driving commercial opportunities with Max Métral  – Senior Analytics Manager Enjoy the show!
45:36
June 9, 2020
#116 Navigating The COVID-19 Landscape: Changes For Data Scientists in the Job Market
In this episode, we hear a panel discussion from Stuart Garland- Director of Blink Recruitment and Data Futurology Director & Podcast Host, Felipe Flores. With the current pandemic drastically affecting the Australian Data Science market, it can feel scary and unknown to people who are looking for a new role or career change within the industry. Read this full episode summary on our website: Navigating The COVID-19 Landscape: Changes For Data Scientists in the Job Market Enjoy the show!
48:36
June 5, 2020
#115 AI Ethics with Stephanie Kelley – PhD Candidate in AI Ethics at Queen's University, IEEE Ethically Aligned Design for Finance Working Committee Member
At Queen's University, Stephanie Kelley is a Ph.D. Candidate in Management Analytics at the Smith School of Business. Her research focuses on the ethics of analytics and artificial intelligence in financial services. She uses methods from management analytics and organisational behaviour to understand the causes and prevention methods for AI ethics challenges. Stay tuned as Stephanie discusses measuring ethics, how countries are taking a stance on AI ethics, and why AI ethics are a competitive advantage. Read this full episode summary on our website: AI Ethics with Stephanie Kelley – PhD Candidate in AI Ethics at Queen's University, IEEE Ethically Aligned Design for Finance Working Committee Member Enjoy the show!
40:21
June 2, 2020
#114 Grokking Artificial Intelligence Algorithms with Rishal Hurbans – Solutions Architect
Rishal is a solutions architect at Entelect. Rishal founded Prolific Idea in 2015, where innovation is cultivated through research and technology. Prolific Idea has since launched a collaborative productivity platform, Hivemind, and is currently building a straight-through document processing platform, Viszen.tech. In this episode, Rishal dives deep into his story and explains how he got involved in the tech industry. Read this full episode summary on our website: #114 Grokking Artificial Intelligence Algorithms with Rishal Hurbans  – Solutions Architect Thank you to our sponsor: Fyrebox - Make Your Own Quiz! And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
38:49
May 29, 2020
#113 Practices of the Python Pro with Dane Hillard – Author and Lead Web Application Developer
Dane Hillard is a software engineer and web developer interested in education, biotechnology, and open source. Today, he shares about the exciting world of web development and how he started. Dane speaks about the future of web development. Read this full episode summary on our website:  >>> #113 Practices of the Python Pro with Dane Hillard – Author and Lead Web Application Developer Thank you to our sponsor: Fyrebox - Make Your Own Quiz! And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
34:32
May 26, 2020
#112 How To Ensure Success In Your Work
Have you ever gone to a meeting to show the outputs of your project, and it goes terribly wrong? When a meeting goes sour, your project gets delayed, or you have to completely restart. If you are meeting with all your stakeholders at once, that is not the real meeting. Instead,  Felipe says to have one-on-one sessions with each of the stakeholders well before the group meeting. This will take more time, but everyone will get dedicated attention. If you do this well before the group meeting, then you will have time to adjust your work. Overall, this will help your stakeholders be more bonded to your project and eventually turn the odds in your favor. Another way to ensure success in your work is by having regular working sessions with your stakeholders. They are working sessions, so you need to be vulnerable and show what you are up to. Make sure the stakeholders know that their input and concerns have gone into your work. This will help develop strong relationships with your stakeholders, and your work will have more impact. Plus, if and when something goes wrong, your stakeholders will be on your side and will likely help you solve it. Enjoy the show! We speak about: [01:30] Why you should have one-on-one meetings with your stakeholders [02:50] Create ongoing and regular update meetings with your stakeholders [05:40] How your stakeholders will help you solve problems Quotes: “Take your stakeholder’s feedback and improve the project.” “Give each stakeholder dedicated time.” “The group meeting is not the real meeting.” Thank you to our sponsor: Fyrebox - Make Your Own Quiz! And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
08:28
May 22, 2020
#111 Machine Learning with TensorFlow with Chris Mattmann – Author / Manager, Chief Technology and Innovation Officer
Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he’s faced at NASA, including building an implementation of Google’s Show & Tell algorithm for image captioning using TensorFlow. He contributes to open source as a former Director at the Apache Software Foundation, and teaches graduate courses at USC in Content Detection and Analysis, and in Search Engines and Information Retrieval. Enjoy the show! We speak about: [00:30] About Chris Mattmann [02:30] How Chris started in the data space [08:15] The transition to management [10:00] How does IT navigate different life cycles of people? [12:35] What’s an example of a bottom-up project? [15:10] How have you seen the importance of machine learning rise? [17:20] Do you have large amounts of data? [21:25] What are the hardware challenges of space? [24:45] About Machine Learning with TensorFlow, Second Edition [30:00] About the Hidden Markov model [34:10] What kept you going through the first edition? [35:40] Why is TensorFlow your favorite framework? [39:00] How do you find time to write? [39:30] What other activities do you do for the community? [41:20] What are you working on at the moment? Resources: Chris’s LinkedIn: https://www.linkedin.com/in/chrismattmann/ NASA Jet Propulsion Laboratory on LinkedIn: https://www.linkedin.com/company/jet-propulsion-laboratory/ Chris’s Twitter: https://twitter.com/chrismattmann Machine Learning with TensorFlow, Second Edition (For 40% off use code poddatafuturology19). Check out other books from Manning Publications, use code poddatafuturology19 for a 40% discount. Quotes: “TensorFlow is everything you need to know about machine learning.” “The thing that kept me going was the realization that AI was the future.” “Python is the data science framework nowadays.” “I see the future.” Thank you to our sponsors: We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Fyrebox - Make Your Own Quiz! And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
46:06
May 19, 2020
#110 Explainable AI Methods for Structured Data
During this special episode, Felipe gives a presentation on explainable AI methods for structured data. First, Felipe talks about opening the black box. Algorithms can be both sexist and racist, even at massive companies like Google and Amazon. Removing bias in AI is a difficult problem. However, there are ways to overcome it. Where does the bias come from? The dirty secret is that the data is biased. The algorithm doesn’t decide to be biased, it learns to be biased from the data. In reality, AI puts a mirror on society. We have inherent sexism and racism in our society. AI is a tool that will help us eradicate these underlying issues in society. No one should be attacking the people that made the algorithms. The data is a representation of the world. We use the explainable methods to interpret what is happening in the algorithms. Explainable methods include explainable algorithms and unexplainable algorithms. When we come across an unexplainable algorithm, we can hit them with a framework and try to make them more explainable. Then, Felipe explains decision trees using the Titanic. Start with a list of all the people who boarded the ship, then separate them by gender. Next, you can use your clear rules to find which passengers survived. The model will give you a good summary of all the data depending on the rules.  Felipe would come across people who said predictable algorithms need to be 99% accurate, or they are garbage. However, if you are predicting how a person will behave, the accuracy will be lower because no one can predict how someone will act. Then, Felipe explains LIME: Local Interpretable Model-Agnostic Explanations. Regardless of the approach, you can use LIME to understand the predictions of an individual person. Stay tuned as Felipe explains the random forest. Enjoy the show! We speak about: [02:10] About Felipe  [04:00] Opening the black box  [07:20] Where does the bias come from?  [11:20] Making more transparent algorithms   [17:00] About decision trees  [19:45] Using interpretable models  [22:20] About LIME: Local Interpretable Model-Agnostic Explanations [30:10] How to use a random forest Resources: #70 Making Black Box Models Explainable With Christoph Molnar – Interpretable Machine Learning Researcher Quotes: “The data represents the way that the world works.” “With the rise of AI, we can choose how we want the world to be.” “Sometimes, we have algorithms that are just 52% accurate.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
37:06
May 15, 2020
#109 Programming, Bioinformatics and the Future of Computer Programming with Ken Youens-Clark – Senior Scientific Programmer
Ken is a senior-level programmer with over 23 years of experience developing software in industry and research environments. Ken is a self-taught computer programmer, software engineer, hacker and teacher. What started off as developing websites in the early 90’s turned into an extensive and fruitful career in bioinformatics and eventually teaching and mentorship. Ken is also the author of Tiny Python Projects published by Manning Publications. Enjoy the show! We speak about: [00:30] About Ken Youens Clark [02:00] Ken’s Work and COVID-19 [03:15] How did you get into the bioinformatics field? [13:00] Ken’s first job in bioinformatics [25:20] How did the design of your book come about? [35:30] How did you keep going despite your frustration with the technology available in early computer programming? [40:35] What are your thoughts on hard coding and data processing? [46:00] What will your next book be about? Resources: Ken’s LinkedIn: https://www.linkedin.com/in/kycl4rk/ Tiny Python Projects (For 40% off use code poddatafuturology19). Check out other books from Manning Publications, use code poddatafuturology19 for a 40% discount. Quotes: “[After COVID-19], the first thing I had to do was become a YouTuber.” “I’m hoping that anyone who is stuck at home right now can watch my lectures, go through the materials, and teach themselves python at home for free.” “That’s all computing is, transforming one thing into another.” “How did you get into that field?”, “A completely random series of mistakes and not knowing what I’m doing” “Anything that [my boss] asked me to do he could have done in half the time and twice as good, but he had the patience to wait for me to catch up” “I fell in love with programming - I was like finally I’ve figured out something that’s interesting, that I truly enjoy doing” “What I see over and over again, especially in science, especially with novice programmers is that everything about the program is hard-coded“ “I haven’t touched a windows computer … since 1999” “[in science/academia] no one teaches programming … you just generally kinda figure it out along the way” “I think people should be taught the basics of command lines; piping, redirecting, those basic kinds of things" Thank you to our sponsors: Fyrebox - Make Your Own Quiz! We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
54:35
May 12, 2020
#108 Should I Become More Technical or Business Focused in my Data Science Career?
If you are trying to choose what skills you should build as part of your career, no single answer fits everyone. It depends on your strengths and ambitions. Your strengths are the things you are naturally good at. If you're not sure what your strengths are, then think about the things that people come and ask you about. When someone asks you how you do something, most likely that is one of your strengths. Also, think about where you want to end up in your career. For instance, if you're going to become a manager, find a way to be a leader on a project and develop your soft influence. Hard influence is something that comes from authority. Whereas soft influence is something that we can build upon. Find a way to lead a project among your peers. Taking the lead will allow you to practice your influence, leadership, and management skills. A group of people will follow the person with an organized and well-thought-out plan; be that person! Another tip - do not be the person that blindly follows what they enjoy; it's not a strategic way to go about crafting your career. Felipe has seen people have a successful career doing work that they enjoy. However, they will eventually lose their love for it. Plus, if you only follow what you enjoy, then you run the risk of getting pigeonholed in an area that may not have future growth. Also, it might be an area that loses demand and importance; it can make your skills irrelevant. At the end of the day, we need generalists. Companies need people who are knowledgeable in the end to end process. As an industry, data scientists are in high demand. Plus, they need people who have a mix of skills. There are always more roles being added because the industry is starting to understand that a great deal of knowledge is required to build a successful data science team. Enjoy the show! We speak about: [01:15] Think about where you want your career to go [03:40] Do not follow what you enjoy [06:25] Why we need generalists Quotes: “Think broadly about what will be needed in the future.” “Overall, the wider you can cast your net when it comes to interests, the better.” “I recommend that you become a generalist if you want to move up.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organization-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
11:48
May 8, 2020
#107 Developing New Products Using Machine Learning with Max Sklar - Engineering and Innovation Labs Advisor and Podcast Host
The Local Maximum is hosted and produced by Max Sklar. Max is a software engineer and new product developer by trade, with a focus on machine learning, Bayesian inference, content discovery, and prototyping. The bulk of his work as a machine learning engineer was at Foursquare, where he built Foursquare City Guide’s critically acclaimed 10-point venue rating system and the Marsbot app. More recently, he led the development of a causality model for Foursquare’s Ad Attribution product and now works at Foursquare’s innovation lab. Enjoy the show! We speak about: [00:30] About Max Sklar [02:00] How did you get into the world of data? [06:05] About the recommender system at Foursquare [10:15] Why do you like solving open-ended problems? [12:20] How has your new role been? [14:20] What are the benefits of staying at a company for a long period of time? [16:30] About Marsbot [20:00] About the attribution side of Foursquare [26:40] How do you pick the innovations you are going to try? [28:50] How does the monthly pitch day work? [31:20] About Local Max Radio Resources: Podcast: https://www.localmaxradio.com/ LinkedIn: https://www.linkedin.com/in/max-sklar-b638464/ Facebook:  https://www.facebook.com/localmaxradio/ Twitter: https://twitter.com/maxsklar Marsbot: https://marsbotapp.com Foursquare: https://foursquare.com Quotes: “Try a few ways and see what works.” “I am looking forward to seeing what kind of trouble people cause.” “I focus on making a splash on pushing forward technology.” “Getting things to work that no one has necessarily tried before - that no one in our company has tried before.” “It's tough to describe probability functions to end clients, it's always good to have that on your side”. Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organization-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
38:55
May 5, 2020
#106 Leveraging Machine Learning and NLP for Conversational AI
Today, Felipe has a few guests at the Data Science Melbourne Meet-Up Group. Former guest Prashant Natarajan and Romina Sharifpour share about their work with conversational AI. Later, Nic Ryan shares his story and tips for getting started in data science. Prashant starts by giving some background on the development and basics of NLP. We have made progress with deep learning and bringing machines closer to understanding human language, but it isn’t easy. Humans have a hard enough time understanding each other. What we are asking machines to do is analyze tone, find nouns, and recognize different languages. We already have things like voice to text and smart speakers, but NLP's ultimate goal is for a bot to have a conversation. True NLP is a combination of natural language understanding and language generation. Enjoy the show! We speak about: [00:10] Introduction & welcome guests [06:45] Basics of NLP & customer service [17:45] Cleaning data and data processing [27:30] Key takeaways from an NLP conventional AI project [42:20] Q&A with Romina and Prashant [51:50] Meet Nic Ryan [53:50] Nic’s start in data science [75:00] Nic’s tips and lessons learned [80:00] The future of machine learning Resources: Data Science Melbourne Meet-Up Group Prashant Natarajan on LinkedIn Romina Sharifpour on LinkedIn Nic Ryan on LinkedIn Check out books from Manning Publications, use code poddatafuturology19 for a 40% discount. Quotes: “When you ask computers to do NLP you are asking them to do something that is the holy grail of machine learning.” “If we don’t make the human's job easier by using NLP then we have to ask ourselves, what the heck are we doing?” “You have to think about what your audience wants, not just what you are interested in” “Consulting is like dating, you meet a lot of people, and there’s a lot of rejection.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organization-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
1:39:42
May 1, 2020
#105 Data Analytics and Marketing with Andrea Ahlemeyer-Stubbe - Director Strategic Analytics and Author
Andrea draws on the wealth of experience gained from her long-standing commitment in the industry, specifically in the areas of Business Intelligence, Data Mining, and Data Warehousing. She studied at the Universities of Dortmund and Sheffield and graduated with a master’s degree in statistics (University Dortmund). In 1999 Andrea branched out to form her own consulting firm rendering personalized services (Business Intelligence, DBM, CRM, and Marketing Services).In April 2012, she took on the role of director strategic analytics, Draftfcb München GmbH, part of IPG Group, now HackerAgency. Andrea’s profound know-how meets the needs of national and international key players in various markets and makes her a frequent lecturer at several universities as well as a well-known speaker at professional conferences. In addition, she is a noted author of two books about data and business. Enjoy the show! We speak about: [00:10] About Andrea Ahlemeyer-Stubbe [02:25] How did you get started in the world of data? [04:00] How has the rise of data and statistics impacted your career? [08:45] Is marketing and analytics something you fell into? Or did you choose to pursue it intentionally? [12:10] What holds people back from trusting data? [15:00] Case Study [21:30] What led you to make the jump to business owner? [26:40] Tell us about your work in China, Japan, and the US [29:45] What surprised you when you started your own business? [32:00] Tell us about your books [40:50] What led you to write your books? [42:30] What advice do you have for listeners in the data analytics space? Resources: Andreas’s LinkedIn: https://www.linkedin.com/in/andreaahlemeyerstubbe/ Monetizing Data: https://www.amazon.com/Monetising-Data-Uplift-Your-Business/dp/1119125138 Practical Guide to Data Mining: https://www.amazon.com/Practical-Guide-Mining-Business-Industry/dp/1119977134 Quotes: “That data you use for prediction should be similar to the data situation where it will be used.” “If people are involved, and you need a decision, it's never done in 5 minutes.” “It’s not just being an expert; it’s clear you have to be that, but being seen as an expert” “Sell your work; they aren’t really interested in the beautiful nice methods.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organization-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
46:55
April 28, 2020
#104 Artificial Intelligence in Retail
In this episode, Felipe speaks about what is going on with artificial intelligence in the retail space. Visual search and recommendations are currently trending in retail. Companies are offering the ability for consumers to search based off of a picture. For instance, consumers can take a picture of a pair of shoes and find that product online, similar products, and products that would go well with it. Humans can process images way faster than text. Plus, pictures carry more information than sound. Visual search and recommendations are hot and on the rise right now. Free shipping and free returns are hurting companies. People are buying multiple items with free shipping and then returning it. As a result, the retailer is paying for transport on both ends. Retailers are struggling with this model. However, free shipping is something that consumers are looking for. So, brands are offering a subscription model or a rental model. Sometimes, a combined subscription and rental model. More and more companies are offering clothing rentals. Next, Felipe explains what to expect in retail. Automated stores are popping up in the United States from Amazon. You pick what you want in the store; then, you walk out without having to see a cashier. With advancements in AI, the movements of customers can be tracked in retail stores. Voice assistance is also something you can expect to see in the future of retail, like ordering something using an Alexa. Stay tuned as Felipe speaks about the basics of AI in retail. Enjoy the show! We speak about: [00:50] What’s hot in retail right now [04:35] The future of retail [07:30] The basics of AI in retail Quotes: Humans can process images way faster than text and they carry so much more information than sound. We can process images in about 13 milliseconds and it’s something that is 60,000 times faster than the equivalent in other mediums. So visual search and recommendations as a result of that search -  that is hot right now and on the rise! Once you get past 20% market share or penetration then you start hitting the mainstream and that’s when the product has fast adoption. What we find is that today’s convenience is tomorrow’s friction. Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organization-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
11:12
April 24, 2020
#103 Advancing Artificial Intelligence with Alberto Roldan - Chief Designer and Artificial Intelligence Officer
Alberto is an analytics executive with hands-on experience in big data analytics strategy, business development, sales, strategic partnerships, IoT, AI, predictive modeling, product design and development, and solution delivery by interacting with executives at the CXO level, acting as a trusted advisor to Fortune 500 companies, and leading data scientists and IT teams. In this episode, Alberto dives deep into his background and explains how he started in the data world. It’s Alberto’s role to advance artificial intelligence in any way possible. He has the skill to put things together from different places. When his parents died, Alberto realized he had a responsibility to use his experience to better other people’s lives. Struggle, doubt, and fear is part of life. However, we need to keep moving forward with artificial intelligence. Alberto has been able to talk to young people about artificial intelligence. He is fascinated with all conversations and curious about everything. Enjoy the show! We speak about: [00:30] About Alberto Roldan [05:20] Why did you pursue law first? [07:30] How do you fuse so many different technologies? [08:40] What led you to your mission? [11:00] What lessons have you learned on your mission? [15:00] How does AI affect us? [20:45] Should companies encourage creativity? [25:15] How will AI merge with consciousness? [28:35] What would you like to see happen with AI? Resources: Alberto’s LinkedIn: https://www.linkedin.com/in/alberto-roldan-4571ba3/ Quotes: “People need to take responsibility to find what is real.” “Have empathy for those who are less fortunate for you.” “Let love and empathy guide us.” “I became used to look[ing] at the world as frequencies, not just binaries” I'm curious about everything “I think that in our busyness of our daily lives that we all have, we really should take time think of how these changes are affecting us instead of riding the wave” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
31:59
April 21, 2020
#102 Analytics in the FMCG Space
Today, industry experts participate in a discussion around analytics in the Fast-Moving Consumer Goods Space (FMCG). We open with a discussion of how millennial preferences have completely changed the FMCG market. Millennials are not typically drawn to one big brand; rather, they are more drawn to hyper localization; everyone wants a personalized product. Additionally, 40% of Millennials check online before even going into a store. All of this has significant implications for the FMCG field. Strategies will need to be developed to understand what people want before it reaches the market. We will see much more localized and customer-led strategies. Some easy to implement areas where we will undoubtedly see changes are: promotional spin, customer segmentation, and industry forecasting. Next, our guests talk about analytic capabilities. We are moving to do fewer things better because shoppers are expecting personalization, but businesses have to continue to be mindful of scale. There are many opportunities for retailers who are hoping to shift to a more centralized model; however, this is only possible if you have reliable data analytics, which enables you to implement things like automatic ordering and work few skews harder. Right now, our biggest challenge in analytic capabilities is how to tie all the data and tools together; we have tools for manufacturing, customer interest etc., but nothing that really ties all those insights together. The next step is to find ways to use advanced data on consumer opportunities at a localized level without losing the power of a company’s scale actually to bring things to the market. We wrap up the conversation with a discussion on promotional effectiveness. Here, the clunky companies are really at a disadvantage. They need to become more nimble and agile but hold the scale that makes them so profitable. Looking ahead, it's clear that purchasing behaviors will change; everyone will shop online. We need to get sophisticated and to the point where we can use promotional analytics to capture metrics like when are people shopping online the most and when are they really spending money. Enjoy the show! We speak about: [02:25] Introduction to Analytics in the FMCG Space [9:45] Key Learnings in Analytics Capabilities [19:30] Opportunities for Retailers [42:00] Data Analytics and Promotional Effectiveness Quotes: “Data is great, but only if you know what to do with it.” “The data assumes that consumers are rational, I assure you, they are not!” In promotional analysis, the art has to meet the science.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
1:11:46
April 17, 2020
#101 Intro to Data Science
Today Felipe gives us a brief but holistic introduction into Data Science. We discuss myths, Felipe’s journey into the data science world, and demystify some of the field's elements. When Felipe started his career, he did not know anything about data science but found himself in the area of machine learning at the Australia New Zealand Banking Group (ANZ). Eventually, Felipe found himself pioneering the first data-driven strategy at ANZ. We learn that one of the biggest myths about data science is the fear that AI will eventually replace humans. Dispelling this myth is possible when we develop a wider understanding of what machine learning actually can and cannot do. First, we need to understand how machine learning works. We learn that machine learning updates the foundational data science process of input (data), algorithm (instructions), and output. Instead, it takes the job of developing the instructions, algorithm, or recipe off of the data scientist. Instead, an algorithm is created based on the data and feedback that is given to the machine. Felipe then dives into an explanation of the two basic types of algorithms, classification, and regression algorithms. Classification algorithms organize categories, and regressions deal with the likelihood of outcomes by shooting out a number from 0 to 1. Felipe spends some time breaking down concepts like AI and decision trees and shares some history of the development of algorithms. Bias data and the importance of understanding how algorithms can be biased are discussed. The power of the decision-making capacity of humans working with machines and data is highlighted. Felipe sees the potential of marrying human judgment and experience with algorithms and data as a game-changer in many areas including the medical field. We close with a Q&A and resources for people hoping to get started in data science, including programs that equip you with the skills and knowledge to get started in the field and include a mentorship program. Enjoy the show! We speak about: [01:25] About Felipe [04:55] What Can Data Science Do & How Does It Work? [17:00] Algorithms [32:00] Key Terms and Decision Trees [46:00] Coupling Machine Learning and Humans [60:00] Q&A and Resources To Get Started Quotes: “In today’s world, everyone should know how to read and write, in tomorrow’s world, everyone should know how algorithms work” “Machine learning can supplement thinking, show you things you haven’t considered, and give you a better perspective that allows you to make better decisions”. “Are humans going to be replaced? Will it always be a combination? That’s up to you.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
1:20:58
April 8, 2020
#100 How To Stand Out in the Data Science Industry
In this episode, Felipe reflects on the past year with Data Futurology. One of the key themes is organizational outcomes. There is a difference between what people find interesting in the data science role and what organizations need from their data scientists. Organizations want to make better decisions based on data. However, data scientists like playing with shiny new toys and using the latest technology. People think about leaving their jobs because it feels like they have used all the techniques that companies have to offer. Mainly, people want to collect algorithms. However, leaders say they have made an impact without knowing all of the algorithms or cutting edge methods. It can be boring to focus on the same algorithms. Organizations need to focus on creating value by solving business problems. If you focus your efforts on solving traditional business problems with new approaches, it’s like a musician learning how to play instruments better. Whereas, data scientists want to learn how to play lots of different instruments. Learning the ins and outs of one algorithm will unlock various opportunities to create value for the organization. Plus, having a more in-depth understanding will allow for more creative applications. You don’t need more data or computing power; you need to be smarter with how you approach problems. Aim to be outcomes-driven and be better at using traditional tools. “I fear not the man who has practiced 10,000 kicks once, but I fear the man who has practiced one kick 10,000 times.” -Bruce Lee Enjoy the show! We speak about: [04:30] Introduction to organizational outcomes [08:25] Creating value by solving business problems [15:15] Change the way you approach problems Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
20:13
April 3, 2020
#99 Utilizing a High-Performance Analytics Database with Irina Farooq – Chief Product Officer
Irina is Chief Product Officer for Kinetica. Irina has over a decade of product management experience across a variety of sectors, including enterprise software, networking, hardware, IoT, SaaS, and Cloud. Irina joins Kinetica from Riverbed Technology, where she held a variety of leadership roles including Vice President of Products and Strategy for the Service Provider Business and Vice President of Product Management for Steelhead, Riverbed's flagship product. Enjoy the show! We speak about: [00:30] About Irina Farooq [01:20] How did you get started in data? [02:50] Why did you switch from engineering to product management? [03:50] What did your career look like after switching to product management? [04:35] How did you learn the craft of being a product manager? [06:20] What type of products were you working on at the time? [08:10] What kept you going during the tough times? [11:25] What has your career looked like after Oracle? [16:00] What challenges did you help customers overcome? [18:15] How do the improvements work? [19:50] What is feature engineering? [24:15] How do you manage the lifecycle of operational models? [30:45] What type of information do you keep track of? [31:20] About Kinetica [34:00] What does a day on the job look like? [35:00] What are your biggest challenges? [37:00] Why did Kinetica decide to go to Australia? [39:30] How does tiered storage work? [42:15] How much has the platform changed? [44:45] What are you most proud of? [49:00] What do you think about challenges in the data space? [50:00] What is a piece of advice for the listeners? Resources: Irina’s LinkedIn: https://www.linkedin.com/in/irinafarooq/ Kinetica: https://www.kinetica.com Kinetica on Twitter: https://twitter.com/Kineticahq Kinetica on LinkedIn: https://www.linkedin.com/company/kinetica/ Kinetica on YouTube: https://www.youtube.com/kineticadb/ Quotes: “Learning and self-improvement kept me going during the tough times.” “The biggest transformation has been being deployed in some of the world’s largest enterprises.” “Figure out what your superpowers are and focus on those things.” “You can’t just fit the mold with everything.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
55:13
March 31, 2020
#98 My Value
During this episode, Felipe talks about how to find and double down on your strengths. Instead of working on your weaknesses, Felipe says that we should do more of what we are already good at. Spend more time thinking about the things that you are talented in. Felipe is good at going and helping teams. Eventually, he makes himself redundant by doing these three things: 1. Sharing knowledge openly, quickly, and effectively. 2. Create a system that is self-organizing and self-sustaining. 3. Helping individuals learn and improve as soon as possible. When working with individuals, find out what their strengths and weaknesses are. Also, learn where they want to go and what they want to know. Then, you will need to understand how they can learn and the ways they can get better. For example, Felipe caught up with a data scientist; he was working on learning his perceived strengths and weaknesses. However, the skills he was working on didn’t line up with a long-term vision for his career. That’s why it’s essential to have a vision in mind. Enjoy the show! We speak about: [01:30] How Felipe makes himself redundant [04:40] Working with individuals in the workplace Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
09:48
March 27, 2020
#97 Productionising Machine Learning Models with Terence Siganakis – CEO, Data Scientist, Software Engineer and Bioinformatician
Terence is a data scientist, software engineer and bioinformatician with over a 15 years of experience working on software solutions to big data related problems in industries as diverse as finance & investment banking, construction, manufacturing, healthcare and retail sectors. Terence is the CEO of Growing Data, a Melbourne based Data Science and Data Engineering consultancy, working with clients such as ANZ, CSL, Metricon and the Victorian Government. Enjoy the show! We speak about: [00:30] About Terence Siganakis [02:30] Marketing Growing Data [04:50] Working with the government [06:30] The numbers behind machine learning [10:00] Why does governance have negative connotations? [11:20] How do you minimize the work upfront? [15:55] How are you tackling big problems? [19:15] How do you stay engaged? [20:40] The way organizations interact with data [22:40] How does Growing Data work? [25:00] Data in the health industry [31:00] Working in finance, health, and construction [34:05] Driving innovation Resources: Terence’s LinkedIn: https://www.linkedin.com/in/terencesiganakis/ Growing Data: https://growingdata.com.au Quotes: “Think about the business outcome.” “Have confidence that what you are building is going to be production-ready when it reaches its targets.” “No one wants to come up with a solution and have nothing happen with it.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
39:18
March 24, 2020
#96 What Data Science and AI Can Do For Your Business
During this special episode, Felipe gives a presentation on what data science can do for business. The CEOs in the audience were from all sorts of industries with companies of different sizes in various stages. Business leaders can use AI to offer new solutions to their customers. Felipe explains machine learning – humans give the input and the output. The machine will do the calculations in-between the input and the output. We can automate a lot of processes using machine learning – it can help us make better decisions, understand human bias, and help us create better businesses. Very few algorithms are 99% accurate. However, they will allow your business to automate decision making and give more insight to make better decisions. Next, Felipe talks about building a data science team. Once you pay people enough, they care about three things: autonomy, mastery, and purpose. Companies are focusing on creating data science products. Most of the value is designed this way; it is very enticing for a data scientist to work in production. Every process that you automate is creating a lot of data that you should be capturing. The ways you can get data is by buying it, scraping it from the web, or collecting it within your organization. Getting information from a different division of your business will improve what you can do internally. Later, Felipe speaks about design-thinking. Find problems that your customer cares so deeply about that they have hacked together a solution. When you find something they care about that has business value, it’s a great place to start. Stay tuned as Felipe takes questions from the audience.  Enjoy the show!  We speak about:  [01:15] About Felipe  [03:30] How does machine learning work?  [07:30] The algorithm will provide insight  [09:30] Building a data science team  [13:30] How to create data  [15:20] The difference between lake, warehouse, and swamp  [18:15] About design-thinking  [20:55] The key points  [22:00] Audience questions  Resources:  Idio: https://idio.ai  Quotes:  “When working with data scientists, get them away from thinking everything needs to be perfect.”  “Machine learning can be used for automation and to make better decisions.”  “Data scientists need to think about the outcome instead of research.”  Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
30:53
March 20, 2020
#95 Enabling‌ ‌the‌ ‌Power‌ ‌of‌ ‌Data‌ ‌to‌ ‌Support‌ ‌Care‌ ‌Initiatives‌ ‌with‌ ‌Leigh‌ ‌McCormack‌ ‌-‌ ‌ Healthcare‌ ‌Analytics‌ ‌Evangelist‌ ‌and‌ ‌Chief‌ ‌Executive‌ ‌Officer‌
Leigh McCormack is a thought leader with 10+ years of experience in developing and applying analytical solutions to complex healthcare problems. She has a deep understanding of data science concepts, methods, and technologies and how to appropriately apply each to accurately and creatively meet objectives. Leigh also has experience building analytic and technical teams from their genesis, through organizational design, and into maturation to the point of demonstrable business value. Leigh is the Chief Executive Officer of Base Camp, a healthcare analytics platform that leverages geospatial analytics, natural language processing, and machine learning to curate actionable social determinant of health insights. Enjoy the show! We speak about: [01:00] How Leigh got started in data [05:00] What data did you look at in clinical trials? [06:00] How can healthcare data be used and reused? [08:30] What type of analytics did you look at in the health care industry? [09:40] How detailed can you go into your findings from the data? [12:20] Were you able to measure health outcomes? [14:15] How was your journey advancing in the company? [16:00] Did your leaders see the importance of data? [20:10] How do you go on a data journey with your team? [22:00] Where else has your career taken you? [24:25] Do you need to sell the social side of data to organizations? [25:55] What type of projects have you been working on this past year? [27:40] How have career transitions been for you? [29:30] What are your other positions, and how do you balance your time? [33:30] Where does your drive come from? [35:40] How do you balance family life and work? [36:40] How did you come up with the idea to start your own company? [39:20] What part of your career set you up to tackle your startup challenges? [40:45] How do you spend your time at work? [42:11] What is a piece of advice you would give our listeners? Resources: Leigh’s LinkedIn: https://www.linkedin.com/in/leigh-mccormack-939a3222/ Base Camp Health: https://basecamp-health.com/ ChaTech: https://chatechcouncil.org/ Women in Analytics: https://womeninanalytics.com/ Quotes: “Healthcare organizations don’t understand the amount of data that they are sitting on.” “Not only do I have to live inside my data science framework, but now I have to master my marketing framework and a sales framework.” “There is something new every day in data science and artificial intelligence.” “Don’t stay in your lane.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
46:05
March 17, 2020
#94 ATO (Australian Taxation Office) Questions
During this special episode, Felipe joins a panel at the Australian Taxation Office. Felipe speaks on four main topics: Improvements in the data industry. Felipe’s views on privacy. Quantum computing and how it will affect machine learning. New developments on AI and how they are impacting jobs. So much of the analytic work we do is to benefit the organization. How do you also ensure data analytics are helping the customer? It needs to be done in a way that is presenting meaningful insight for the individual. For instance, car technology today comes with a range of sensors and cameras that are making decisions. However, this data isn’t being collected and reported back to the customer. Grocery stores are also collecting data and using it to make predictions. For example, stores know when their consumers will need to buy toilet paper. The stores should be sending a reminder to their consumers by reusing the data they already have. Then, Felipe discusses ethics in artificial intelligence. Algorithms are consistently being deemed racist and sexist. We need to realize that the algorithm only learns the bias because the bias is in the data. When we find these errors, we can have tough conversations and improve the algorithms. Later, Felipe talks about how AI is impacting jobs. For instance, AI is now creating custom videos and articles for popular news websites. On one side of the argument, we are going to have a much more efficient economy. While on the other hand, many people say we are going to lose jobs. Felipe says that most jobs will be enhanced by AI instead of being replaced by AI. Enjoy the show! We speak about: [02:55] Making data analytics benefit the customer [11:30] Ethics in artificial intelligence [14:20] Felipe’s views on privacy [16:30] Quantum computing and how it will affect machine learning [19:00] How AI is impacting jobs Resources: ATO: https://www.ato.gov.au Quotes: “The same data that is prepared for the organization can be taken to benefit the consumer.” “The data is biased because it is a representation of our world.” “I think that the discussion around privacy heightens when we move it away from value.” “Jobs will be enhanced by AI, not replaced by AI.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
22:40
March 13, 2020
#93 Making Analytics Matter For Your Customers
During this special episode, Felipe speaks at the IAPA National Conference. His presentation focuses on making analytics matter for your customers. More specifically, Felipe speaks on these topics: About organizations making a mindset shift. How analytics professionals can leverage the work they do. The ways we can add value to the end customer. Many companies claim they put customers first, but how do they show it? Companies have heaps of data on their customers. The next wave of companies that do great will actually show customers that they care about them. There are three simple ways to use analytics for your customers: Benchmarking. For instance, when a student gets a test back. What percentage of students did better them? Benchmarking is often overlooked, yet it can provide excellent value to the customer. Predictions and forecasts. We have loads of data on our customers to benefit the business. However, automated tools can redirect the data and use it for the benefit of the customer. Key drivers. Everyone wants to be better. We can give our customers feedback on how they can be better and achieve the goals that they have. Felipe uses grocery stores as his first example of how to implement these three steps. If the app sees you are buying pasta and sauce, they can offer their customer free garlic bread as a gift from the store. It’s a personalized and unexpected gift. The algorithms will also know when their customers are going to need toilet paper. This information is valuable to the company. It can be valuable to the customer because they can send a reminder to the consumer’s app. What do customers want? They want some perspective in their lives. What’s something about the customer you can inform them about that they don’t already know? Stay tuned as the audience asks questions to Felipe. Enjoy the show! We speak about: [01:40] About Felipe [04:10] Developing a relationship with your customer [06:30] Three ways to use analytics for your customer [12:50] Grocery store example [15:50] Car example [20:55] Business owners can also use analytics [24:30] What do the customers want? [27:15] Questions from the audience Resources: IAPA: https://www.iapa.org.au/advancing-analytics Quotes: “Five to seven percent of the data that is being captured is actually getting used.” “We can get more intimate with our services once we focus our value on the customer.” “Start with the data that you already have from the customers that you already have.” “There is a risk of being creepy when you have too much data on someone.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
34:58
March 10, 2020
#92 People Management, Seeking Feedback, and Navigating Office Politics in Data Science with Barrett Hasseldine – Head of Modelling
Barrett Hasseldine has held several leadership roles within the field of Data Science / Analytics. With a BSc majoring in Mathematics and an MBA, he is passionate about bringing mathematics and business closer together. In particular, he loves converting business problems to math problems, guiding analysts to solve the math, then converting the mathematical solution into a set of business actions that drive quantifiable business value. During his career, he has delivered analytic solutions in the domains of Credit, Fraud, Marketing, Politics, and Operations. Enjoy the show! We speak about: [00:30] About Barrett Hasseldine [01:20] How did you get started in the world of data? [02:55] Why did you pick operations research? [08:55] Do you find that people are thinking about business decisions affecting the model? [10:30] When were you able to see business problems in the math problems? [15:20] How do you turn the work environment into a positive feedback loop? [18:30] How did the opportunity come for you to step into management? [21:55] What would you change about your management techniques now? [25:00] How are you open to feedback? [26:45] How do you bring feedback out from people? [28:40] What do you think about imposture syndrome? [29:25] How did your career evolve after becoming a manager? [33:55] What would have made you better prepared for management? [39:30] What does the process look like when creating a new product? [42:00] How do you work with other teams? [42:50] How do you measure the demand for a new product? [49:35] How have your career goals changed? [52:00] What is a piece of advice you have for the listeners? Resources: Barrett’s LinkedIn: https://www.linkedin.com/in/barrett-hasseldine/ Manager Tools Podcast: https://www.manager-tools.com/all-podcasts Quotes: “People don’t follow equations.” “You learn from the people that you’ve had as bosses in your past, and you learn from your own experience.” “I’ve always been a fan of continuous learning. I’m open to feedback and use it to change continually. “The absence of imposture syndrome is an issue.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
55:47
March 6, 2020
#91 Researching the Social Impacts of Technology and Artificial Intelligence with Mary L. Gray – Senior Principal Researcher, Author, and Professor
Mary L. Gray is a Senior Principal Researcher at Microsoft Research as well as an E.J. Safra Center for Ethics Fellow and Berkman Klein Center for Internet and Society Faculty Affiliate at Harvard University. Mary also maintains a faculty position in the School of Informatics, Computing, and Engineering with affiliations in Anthropology and Gender Studies at Indiana University. Mary, an anthropologist and media scholar by training, focuses on how everyday uses of technologies transform people’s lives. Enjoy the show! We speak about: [00:30] About Mary L. Gray [04:25] What’s it like in the Microsoft Research Center? [06:25] What surprised you the most about researching with Microsoft? [08:40] Is your work focused mostly in the United States? [10:10] Is your previous work focused on the social side of technology? [14:40] What other interesting viewpoints did you learn during your research? [24:00] How are people’s work lives being shaped by AI? [35:30] How is automation going to affect the execution of algorithms in specialized fields? [42:40] How do you see AI evolving in different countries? Resources: Mary’s Website: https://marylgray.org Mary’s Twitter: https://twitter.com/marylgray Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass In Your Face: Stories from the Lives of Queer Youth, Queering the Countryside: New Directions in Rural Queer Studies Out in the Country: Youth, Media, and Queer Visibility in Rural America Quotes: “I love studying gender and sexuality because it is so intimate.” “If we are constantly interacting with each other, we can constantly transform into different senses of who we are.” “When you introduce new technologies, it is shaping conversations.” “The work of data science is a global project.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
48:56
March 3, 2020
#90 Solving Master Data Challenges for Large Global Enterprises with Scott Taylor – Data Whisperer & Principal Consultant
Scott is a firm believer in “making your data do the work,” and he has enlightened countless business executives to the value of proper data management by focusing on the strategic rationale and business alignment rather than technical implementation and system integration. Scott is more of the strategic WHY than the technical HOW. He has spent over two decades guiding Tech Brand owners to leverage their reference data and taxonomy assets. In a variety of strategic marketing, GTM, innovation, and consulting roles, Scott has worked with some of the world’s most iconic business data brands, including Dun & Bradstreet, Nielsen, Microsoft, Kantar, NPD as well as start-ups such as Qoints and Spiceworks. Enjoy the show! We speak about: [00:30] How Scott started in the world of data [04:30] How did you develop your engaging videos? [07:50] How have you seen data change over time? [11:30] What are people not understanding about MDM? [16:35] What are the classic pitfalls? [19:45] Is master data similar to data engineering? [21:00] Do people struggle to talk about data as an asset? [25:50] How are you having the best time in your career right now? [30:55] What’s the philosophy behind your content? [38:30] How did you land on the Data Whisperer and Meta Meta Consulting? Resources: Scott’s Website: http://metametaconsulting.com Scott’s YouTube: https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw Scott’s Twitter: https://twitter.com/stdatawhisperer Scott’s LinkedIn: https://www.linkedin.com/in/scottmztaylor/ Quotes: “You need data management first before you do business intelligence.” “I’m the sous chef in the back, making sure we have the right ingredients.” “Do upon your data as you would have it do upon you.” “Master data is your most important data.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
47:08
February 28, 2020
#89 Starting an AI Company After Building Six Other Businesses with Emrah Gultekin – Co-Founder and CEO
Emrah Gultekin is the co-founder and CEO of Chooch. Chooch AI is a complete visual AI platform with an API, a dashboard, and a mobile SDK. Combining computer vision training with machine learning, Chooch offers object recognition and facial authentication, with autonomous labeling, data collection, neural network selection, and more. Chooch is used in the media, advertising, banking, medical, and security industries. Enjoy the show! We speak about: [00:30] How Emrah started in the world of data [03:00] What is the inspiration behind your company? [05:00] How did you meet your co-founder? [06:45] How do you tackle disagreements with your co-founder? [08:00] Did you de-risk your life from the start-up? [11:00] About Emrah’s products [14:00] Case study examples [20:20] What makes Chooch different? [23:30] Do you have methods to prioritize your labeling? [30:40] What has surprised you the most about Chooch? [33:40] When did you decide to move to Silicon Valley? [34:30] What are you working on now? [36:15] Advice for the listeners Resources: Emrah’s LinkedIn: https://www.linkedin.com/in/emrah-gultekin-6123ab1/ Chooch: https://chooch.ai Quotes: “We automate the labeling process – that has been a key thing to scale.” “No data is perfect.” “We have to understand that bias is a natural state.” “The more you know about something, the more critical you will be.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!
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February 25, 2020