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

We are joined by José Murillo, Chief Analytics Officer at Grupo Financiero Banorte, Mexico's second largest financial group and also the most profitable one pre-pandemic. José had a long tenure at Mexico’s Central Bank, where he worked at the research department. Around 7 years ago, he joined Banorte and established the Analytics Business Unit. His efforts delivered profits equivalent to 46x the cost  just within the first year and almost 250x their cost last year. During his time there, he has helped the bank go from the fourth to the second largest financial group in Mexico, surpassing companies like Grupo Santander and CitiBank. Quotes: "The idea was to build this data science team and I think it was a blessing in disguise at the time, in the sense that they funded the group, but I think there were still some doubts of what would be the yield of bringing people different from what the group used to have. They said "Yes, we are going to fund it but in a year time you need to deliver 10x your cost. It seemed quite steep because for a traditional business they were asking 3x the cost. Long story short, within the first year we delivered 46x the cost and last year we were close to 250x our cost." "We were built to deliver profits and I think that helped us focus on things that were valuable to the organization and to be accepted because we were bringing value." "I’ll be honest, I was a bit overwhelmed when they told me that I needed to make 10x my cost in a year and I was a bit reluctant to accept the challenge. My boss told me ‘you’re not going to have a problem, just go and look at the amount of resources we have on the credit card business. You’ll be fine.’" Thanks to our sponsor Talent Insights Group Read the full episode summary here: Ep 149 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Today we are joined by Doug Laney, Data & Analytics Innovation Fellow at West Monroe and Author of "Infonomics". Nearly two decades ago, Mr. Laney originated the field of Infonomics, developing methods to quantify information's economic value and apply asset management practices to information assets. He authored the book "Infonomics: Monetizing, Managing and Measuring Information as a Competitive Advantage," and lectures at leading business schools on the topic. In addition to his dozens of Gartner research publications and blogs, Mr. Laney is a contributing author with Forbes and Information Management Magazine, and has been published in the Wall Street Journal and the Financial Times. He also edited and co-authored Forbes' e-book on Big Data. He was a vice president and distinguished analyst with Gartner's Chief Data Officer (CDO) research and advisory practice. He is an accomplished practitioner and recognized authority on data and analytics strategy, and is a three-time recipient of Gartner's annual Thought Leadership Award, and is regularly considered one of the top global influencers these topics. Mr. Laney specializes in and assists organizations with data monetization and valuation, open and syndicated data, data governance, and big-data based innovation. In 2001 he coined the "3Vs" of volume, velocity and variety, now commonly used in defining Big Data. Thanks to our sponsors Talent Insights Group Read the full episode summary here: Ep 148 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We have Kevin Buckley, Founder and CEO of Torrey Pines Law Group, PC in San Diego, USA. He joins us for an insightful chat on Life Sciences and AI. He created Torrey Pines Law Group when he returned home to San Diego in 2013. Throughout his career, he has successfully represented pharmaceutical, biopharmaceutical, medical device, biotechnology, specialty chemical, digital health, healthcare software, artificial intelligence, and convergence technology clients for more than 20 years. Quotes: "If you got a patent on something you can’t detect the infringement of, then why get a patent in the first place, maybe keep it trade secret or as a small subset of trade secret law. Early on you need to decide what you want to do." "IP does not exist in a vacuum. IP affects so many different other areas of law, business and science to some degree. Also, different laws, business and science also impact IP law, so it is completely integrated with every other facet of law." Thanks to our Sponsor Talent Insights Group Read the full episode summary here: Ep 147 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We have Calvin Ng, Head of Equality and Linking at Equifax and Patrick Choy, Senior Consultant at Talent Insights Group. Today we are focusing on teams. Everything from hiring, how to structure them, retention and more useful tips. Patrick shared some tips for data scientists who want to differentiate themselves when going through recruitment processes. For him, communication is key and he encourages people to communicate their past successes and show the recruiters how they could use that knowledge and experience to create a positive impact for their business. We touched on how some jobs may be advertised as data science roles and once hired, individuals realize the work needed to be done is not what they expected or part of the data field. Companies don't always have a good handle on exactly where they sit in the data maturity curve and many of them are still very much starting their data journey. For Calvin, this is an exciting opportunity for professionals who are willing to take on the challenge of helping them create their data science teams and structure from the ground. As individuals continue to upscale their skills and organizations try to involve more data science in their processes, the field and competition in it will grow, so stay tuned to hear insightful tips from Australia’s leading data specialist recruitment business, Talent Insights. Quote: The high performing team is the team who trust each other, learn from each other and has a diverse set of skills and viewpoints. Thanks to our sponsor Talent Insights Group Read the full episode summary here: Ep 146 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Doug Farell is the Senior Web Engineer at Shutterfly and Author of The Well-Grounded Python Developer, he joined us as our first live webinar guest back in January. Doug has more than 20 years of software development experience in several industries and disciplines. Having been in the industry for many years, Doug fully embraces the concept that "change is the only constant" and can take advantage of emerging technologies and demonstrate the benefits of new technologies to co-workers and management. He has a real passion for technology and that becomes evident in his book The Well-Grounded Python Developer. Thanks to our Sponsor Talent Insights Group Read the full episode summary here: Ep 145 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Alexey Grigorev for an episode that will be very useful for anyone wanting to identify the skills needed to get into the data science world. Alexey works as a lead data scientist at OLX Group, where he deals with content moderation and image models. He is an experienced software engineer with 10 years of experience. In the last 6 years, he focused mainly on different aspects of machine learning. Previously he successfully competed in many data science competitions and wrote a few books about machine learning. One of them is Machine Learning Bookcamp — a book for software engineers who want to get into machine learning. Thanks to our sponsor Talent Insights Group  Read the full episode summary here: Ep 144 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We have Matthew Dixon, Assistant Professor of Applied Math at the Illinois Institute of Technology and author of the textbook, Machine Learning in Finance: From Theory to Practice. He has also written several journal papers on algorithms and models for machine learning, blockchain based technologies with applications in fintech.  Quotes:  "Do you want uncertainty as your first class citizen or do you want it more as an afterthought?"  "You had to fit models to the data. I realised quickly that was the achilles’ heel for the approach."  "It isn't just a guessing game."  "In the Bayesian world, it sort of turns everything on its head. It says every parameter in your model is a source of error."  "I think interpretability is a must. Not only to appease regulators or non technical finance professionals but rather when something goes wrong."  Thanks to our sponsor  Talent Insights  Read the full episode summary here: Ep 143  Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Merve Hickok, Founder of AIEthicist.org, joins us today to share her knowledge on AI Ethics. She is an independent consultant, lecturer and speaker on AI ethics and bias and its implications on individuals & society. She creates awareness, builds capacity and advocates for ethical and responsible AI while also collaborating with several national and international organizations building governance methods. Thanks to our sponsor  Talent Insights Group  Read the full episode summary here: Ep #142 Enjoy the show!  --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Michelle Perugini, she is the co-founder and CEO of Presagen and Life Whisperer. In 2017, she had the opportunity to combine her passion for healthcare and technology and started Presagen, an amazing company that's doing things that actually change people's lives. Presagen is both a platform and product company. They have a really unique AI platform that helps them build scalable AI medical products. One of those products is Life Whisperer, which uses AI for the embryo selection during the IVF process. Instead of having an embryologist looking down a microscope at your embryos and doing a visual assessment, this gives them the ability to use AI as part of the decision process. Quotes  If I didn't happen to have that opportunity I may never have taken that step and wouldn't have this amazing career path that I've been able to have and that I'm really passionate about. We were young, we had no commitments, we didn't have a family, so we thought why not? If we're going to do it, might as well do it now. So we did. Thanks to our sponsor: Talent Insights Read the full episode summary here: Ep #141 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this episode we talk to Tyler Folkman, Head of Artificial Intelligence at Branded Entertainment Network.  Tyler joined Branded Entertainment Network almost two years ago and ever since has been working on how to leverage AI and data in the world of entertainment, specifically product placement. Their work is similar to that of a recommendation algorithm in that they use data to connect brands with the right creators to offer their audiences relevant products. They help brands find the best partner possible across different platforms like TV, YouTube, social media, etc. His main goal is creating value for the company with data and he has built a team that shares this belief with him and helps him make it possible.  Quotes: "I really am a big believer in data scientists being able to own the process, all the way from data collection, cleaning, modelling, to deployment and even creating web applications. The data scientists on our team can deploy their own models and create front end interfaces so that someone on the team can come and play with the model that is not a data scientist can see what the predictions are and see if it makes sense. And we found when creating a platform for data scientists to do that, it allowed them to work much more efficiently. " "I have seen people fail sometimes if you treat it more like an assembly line where data scientists only model, they just get blocked too much and they have to rely on so many teams to get value. It just never works in my experience." Thanks to our sponsor: Talent Insights  Read the full episode summary here: Ep #140  Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We have Carlos Avello, Marketing Science Lead at Amazon (Director of Marketing Analytics at eBay at the time of recording) joining us for an insightful chat on Causal Inference and how it can help businesses understand causes and impacts for better decision making. Even before ecommerce started, Carlos was already working within an extremely data-driven business model. He started his journey in direct response marketing, tracking data from coupons and later analyzing it. In his own words, he explains causal inference is based on evidence you collect of the impact a certain marketing effort had on your overall sales. Experimentation is the core of causal inference, and specifically A/B tests are used very often. Quotes: "Causal inference is based on evidence you collect of the impact a certain marketing effort had on your overall sales." "Experimentation is at the core of it. You cannot get into causal inference if you do not compare two different populations with different treatments." "Marketing is the product of a partnership between the advertiser and the advertising platform. Two different companies and there are things that we are ready to share and some others that are tricky to share, like customer data. If you want to setup a test where you are suppressing treatment to some people and allowing others to be exposed to the treatment and then compare the final results on sales you need to find a solution were you are saving enough information so the advertiser knows who has been exposed and who has not and later they can compare the sales." Thanks to our sponsor: Talent Insights Read the full episode summary here: Ep #139 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Aurelie Jacquet, Chair of Standards Australia, an independent not-for-profit organisation that specializes in the development and adoption of internationally-aligned standards in Australia. Aurelie is an expert in governance, data ethics, privacy and responsible use of technology. She starts by sharing with us how her journey in the data and ethics world started. She is a lawyer by trade, who started as a litigator and then moved on to work in finance for algorithmic trading. Her interest in AI and ethics peaked in 2016, she soon realized all law initiatives regarding AI were done overseas, so she decided to venture into the world of standards and push for Australia to participate in the international standards around AI. Quotes: "A use case I see that keeps coming back is 'how do you manage privacy, bias and accountability?" "The solution you use to address fairness and bias should strongly align with the legal principles of fairness and bias." "If you don't have the right control in place, or the right filters, then your output can be problematic." Thanks to our sponsor: Talent Insights Read the full episode summary here: Ep #138 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We’re starting 2021 with Silvio Giorgio, GM Data Science & Strategy at Australia Post. He is an energetic senior leader appointed by the Group CFO to disrupt finance from within. Silvio establishes and leads Data Science for Australia Post applying artificial intelligence, machine learning, predictive modelling, robotics and much more to improve people's safety, customer experiences and commercial outcomes. He was named #1 in the #IAPA Top 25 Analytics Leaders Program 2020. Quotes: "We’re not doing dashboards anymore." "If this is where the future is, then what are you going to do?" "It popped into my mind the concept of doing magic with data. And it wasn’t about what we would do, it was about what people would see. We needed to make people excited about it, we needed to make people think it was magic and want to see more, to sparkle the curiosity that magicians do." Thanks to our sponsor: Talent Insights Read the full episode summary here: Ep #137 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In our last episode, we have Alan Ho, Head of Global Partner Marketing at Tibco Software. We look back on the challenges brought by this year and, as it comes to an end, we reflect on what we need to do differently moving forward and what areas offer hope to those who wish to participate more actively in the data economy. As a part of today’s discussion, we also had the pleasure of chatting with Sara Tiew, Public Sector Leader & Job Redesign Practice Leader at Mercer around the topic of the future of work. Sara acknowledges the fear people have of losing their jobs due to technology and automation, but she clarifies that technology will also create several million new jobs. Therefore, it’s extremely important to help workers employed in roles that are at risk and transit them into new job opportunities available. Quotes: "When I look at diversity I am not just looking at gender diversity, I’m looking at cultural diversity. I’m looking at orientation diversity." "I want to spend my time giving back to society and what can I do in my capacity to support those that require this help." "The Pandemic has brought forward digitization. It has impacted such a great deal in countries that are not ready will face a bigger challenge, especially from a skillset perspective." "If you look at banking and tech sectors, they are always at the forefront of adopting technology." 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 12 Enjoy the last episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Disha Goenka Das, Director of Marketing at Twitter APAC to discuss the modern CMO's job. Disha has had a great career in marketing and has experience in several areas like sales, operations, product management and product marketing. She describes herself as endlessly curious and always wanting to explore the world. Creating marketing strategies and campaigns purely for customer delight is her happy place. She acknowledges technology is moving at a dramatic pace, and marketing is one of the most technology-dependent business functions, so she advises all marketing professionals to make a disciplined effort in staying up to date with the new technologies coming along. Quotes: "If I had to give advice to anyone who is in marketing I would say that marketing and technology are moving at a dramatic pace, it’s moving at a faster pace than any of us ever predicted. Keeping ourselves up to date requires structured learning and working. Whether you are a CMO today or you are a marketing manager you have to make sure that there is a disciplined effort in learning the new tech that is coming as we move along. That is one thing that will be critical for marketing professionals to succeed going forward." "The other advice I would give for any young marketing professionals starting out in marketing right now is, looking back from my experience, try to spend some time in sales to try to understand the end customer and figuring out what they really care about. Also, on the product side to understand, for example, how engineering makes product decisions. I truly believe it makes you a better marketer. Whether you can do that through rotation programs or spend a year or two in these roles, it is going to be super critical for understanding the business’ core." "I feel CMOs need to be both analytical and creative. Exceptionally successful CMOs who are at the leading edge of technology, deeply first understand the questions that they’re trying to answer, work with data to figure out how to answer it and most importantly, how do they use that information and data to bring it to life in a way that is truly beneficial. That balance is something important and I don’t see it going away despite how much AI and ML comes into the world." 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 11 Enjoy the eleventh episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message