DiscoverData Futurology - Data Science, Analytics, Machine Learning and Artificial Intelligence For Leaders
Data Futurology - Data Science, Analytics, Machine Learning and Artificial Intelligence For Leaders
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Data Futurology - Data Science, Analytics, Machine Learning and Artificial Intelligence For Leaders

Author: Felipe Flores

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Data Futurology is data science from a human lens.
In Data Futurology, experienced Data Science Leaders from around the world tell us their stories, challenges and the lessons learned throughout their career.
We also ask them:
- What makes a great data scientist? What skills are required?
- How to become a great data science leader?
- How should I grow and get the most out of my team?
- What is a good data strategy? and how do I best implement it?
- What are interesting applications of ML/AI that I should be considering in my industry?
To find out more visit www.datafuturology.com
78 Episodes
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Tony believes that analytic innovation and creativity come from experts directly collaborating with clients on their projects. He joins AlphaZetta with a mission, to create a better way for independent experts to work directly with clients, lowering the costs and opening access to high quality analytics talent to a wider audience. He brings 20 years of deep practical experience globally. He has held senior positions with clients and large consulting firms. He has won several awards for innovation in analytics including as a Finalist for Australia’s Young Businessperson of the Year Awards.Enjoy the show!We speak about:[02:00] How Tony started in the data space[04:00] What Tony’s journey has looked like[05:30] Comparing data and analytics in different countries[08:30] How was the adoption of the data infrastructure in China?[11:10] How did ICBC gain new users?[12:25] What are you most excited about?[14:00] How can you bring data ethics to life?[18:40] Any surprises when practicing data ethics?[20:20] How have people jumped on board with data ethics culture?[22:15] What was it like to build a bank with analytics at its core?[27:00] About AlphaZetta[32:20] What problems does AlphaZetta like to tackle?[34:10] How does consulting work at an analytics company?[35:30] What surprised you the most with AlphaZetta?[37:00] Have you been involved in early-stage companies previously?[39:15] Lessons learned from previous work experience[41:00] What does the decision-making process look like in analytics?[42:40] The visions for Volt Bank and AlphaZetta[44:30] What would you like to be known for?[47:00] What are the current and future challenges for the industry?[50:20] What are you most proud of?[51:25] A piece of advice for our listenersThank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Angela Wilkins is the founder and Chief Scientist at Mercury Data Science (MDS) where she works with Mercury's portfolio companies to identify solutions for complex data problems. Prior to MDS, Angela was a member of faculty research at Baylor College of Medicine and led projects at the policy think tank, Center of Science and Law. She developed her machine learning knowledge in the biomedical field as part of IBM's Watson AI and DARPA Simplex Project. Angela received her M.S and Ph.D. from Lehigh University, all in Theoretical Physics. Enjoy the show!We speak about:[01:10] How Angela started in the data space[03:45] Using proteins to understand aging[07:35] Setting team expectations[09:15] Challenges at Baylor[15:15] Using data science to make policy[18:30] Leading seminars on machine learning and data science[22:05] TrendKite – putting the right data in front of the PR person[26:40] The transition from academia into business[30:15] Rapid fire questions[35:00] Future data science challenges[36:10] Do as many things as you canResources:Angela’s LinkedIn: https://www.linkedin.com/in/adwilkinsMercury Fund: https://mercuryfund.comTrendKite: https://www.trendkite.comQuotes:“We look to see how proteins, drugs, and diseases interact.”“We came up with an algorithm for aligning protein networks along multiple species.”“I left Baylor because I needed new problems.”“Algorithms are useful everywhere.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Michael Brand has over 25 years of cutting-edge, international industry experience in advanced analytics, machine learning, artificial intelligence, machine vision, and natural language processing, Dr. Brand’s data expertise is both uniquely wide and uniquely deep. He served as Chief Data Scientist at Telstra Corporation, as Senior Principal Data Scientist at Pivotal, as Chief Scientist at Verint Systems, as CTO Group Algorithm Leader at PrimeSense Ltd (in the machine-vision team that developed the Xbox Kinect), and as Director of the Monash Centre for Data Science in his role as Associate Professor of Data Science at Monash University. He has developed solutions at every scale from on-chip to Big Data, from real-time to high-powered computing, and made industry-defining contributions that have earned him 16 patents (more pending), garnered many prestigious industry and academic awards, and underline $100Ms/pa revenues and $100Ms in valuation for the companies he worked with.Enjoy the show!We speak about:[01:45] How Michael started in the data space[05:35] Capturing brand new blood pressure data[09:15] What you buy and eat depends on the weather[15:10] Working with data science in the Israeli army[19:40] Engineering approach vs. the scientific method approach[28:45] When is the deep learning madness going to end?[31:00] Working at Verint Systems[36:05] The core of what Michael currently does[43:20] Tools to ensure secrecy[47:20] Making strategic decisions with data science[50:00] Every company needs a data strategy[54:15] Where does data governance play a role in an organization?[63:10] The need to start talking about data rights[69:20] Listener questions[76:00] Michael has imposter syndromeResources:Michael’s LinkedIn: https://www.linkedin.com/in/michael-brand-b230736/Otzma’s LinkedIn: https://www.linkedin.com/company/otzma-analytics/about/Otzma Analytics: https://otzmaanalytics.comQuotes:“When you have data that nobody has ever looked at before, you will see stuff that nobody has ever seen before.”“We are in a world where we are pushed towards thinking of data science as a form of engineering.”“You can outsource a lot of things, but you should do your own testing.”“Every data you encounter is different; the value is understanding how that data is different.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Amy is an Engineer and a multidisciplinary Data Scientist at USAA. She received her B.E degree in Electrical and Computer Engineering at the University of Minnesota and her M.S. and Ph.D. degrees in Electrical Engineering from the University of Texas. Amy is an active promoter for women in STEM and enjoys teaching & organizing community events to increase women's visibility in the field. She previously served as the Women in Data Science Ambassador (WiDS) for the Global Women in Data Science group at Stanford University. She also founded San Antonio Data Science Meetup in 2016.Enjoy the show!We speak about:[02:55] How Amy started in the world of data[05:40] Amy’s professional background[07:40] Amy’s Ph.D. changed everything[13:00] Deciding to become an entrepreneur[17:45] Having kids inspired Amy to work in healthcare[25:20] Amy’s passion has kept her motivated[27:50] Being a female in the data space[35:40] About the Women in Data Science Meetup[42:00] Having a work/life balance[44:25] What Amy is most proud of in her career[49:30] Amy’s advice for aspiring data scientistsResources:Amy’s LinkedIn: https://www.linkedin.com/in/amywdaali/Amy’s Twitter: https://twitter.com/wdaali999?lang=enLucea AI LinkedIn: https://www.linkedin.com/company/lucea-ai/about/Lucea AI Website: https://www.lucea-ai.comWomen in Data Science: https://www.widsconference.org/ambassadors-2018.htmlSan Antonio Women in Machine Learning & Data Science: https://www.meetup.com/San-Antonio-Women-in-Machine-Learning-and-Data-Science/events/IEEE Smart City Summit: https://attend.ieee.org/scs-2019/speakers/Quotes:“Data has the ability to help a lot of people.”“If you can do a Ph.D., you can do anything.”“I love the fast pace of the industry.”“You don’t need a PhD to be a data scientist.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Ru is a graduate from the University of Cambridge, UK who has built six startups in four countries. His primary interest is to build products with social Value. He is also a mentor of Google Launchpad and a senior AI advisor of EFMA Banking group. Ru has been invited to speak at over 60 events from 21 countries. His talks are about sharing his experiences on growing various startups and building products in Artificial Intelligence and Machine Learning.Enjoy the show!We speak about:[01:45] How Ru started in the AI space[06:50] What surprised Ru about startups[10:15] Getting data first, then finding customers[15:00] Ru’s writing career[18:35] How to live a complete life[20:40] What success means to Ru[31:10] Bringing to life the machine learning models[35:00] Ru’s advisory roles[39:00] OpenAI[41:20] Overcoming challenges with data[44:00] Challenges with user adoption[50:00] What Ru is most proud of[51:40] Advice for the audienceResources:Ru’s LinkedIn: https://www.linkedin.com/in/mitrarRu’s Website: https://www.mitrarudradeb.comCreating Value With Artificial Intelligence: Lessons Learned from 10 yrs of Building AI Products and Overcoming Data, Adoption, and Engineering ChallengesQuotes:“I overcome challenges by learning from my failures.”“Two years ago I would have never thought I would be a good public speaker.”“Success cannot be defined by external factors.”“I haven’t been stressed for three years, maybe more.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Alex Ermolaev has been involved in the software industry for 20 years, including AI-specific experience at Bell Labs, Microsoft, several startups and now Nvidia. He is currently a leading AI software developer and works with groundbreaking companies that are implementing incredible AI solutions across several domains.In this episode, Alex describes how he started in the data space. Early in his career, he got a chance to work on a lot of data and software products.Enjoy the show!We speak about:[01:50] How Alex started in the data space[04:55] Alex’s professional background[10:30] Working for the finance team at Microsoft[14:55] Business development skills[18:50] Challenges working with startups[22:10] Working at Nvidia[26:20] Successful and unsuccessful AI patterns[30:00] AI and collecting data[35:15] How to tackle data problems using AI[40:30] Exciting uses for AI[43:15] The execution of new AI programs[49:00] What Alex is most proud of[50:20] Be patient and invest in your knowledgeResources:Alex’s LinkedIn: https://www.linkedin.com/in/alexermolaevQuotes:“The best way to develop knowledge in any area is to experience it.”“It is easier to sit in an office and assume the world works in a certain way.”“Don’t be in startups because it’s cool, try and find a path that meets your own needs.”“Working with startups is a lot of broader outreach and helping the community understand what is possible.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Evan Shellshear has been an entrepreneur for more than a decade, and throughout that time he has always loved getting his hands dirty with building products from scratch and then commercializing them. Evan has a passion for innovation and not just from a managerial perspective but also from a doing perspective. He has a Ph.D. in Game Theory, is published in fields computer graphics to politics, mathematics to manufacturing, and much more. Evan has founded or co-founded over half a dozen companies to commercialize different technologies.Enjoy the show!We speak about:[01:15] How Evan started in the world of data[09:45] Zoom out to solve technical roadblocks[12:10] Examples of how Evan zoomed out[14:25] Why is zooming out a challenge for data scientists?[18:00] Focus on simplification[22:45] Taking opportunities that present themselves[27:00] Measures of success during a project[31:00] The process of a case study[36:05] Getting users to adopt new technologies[40:00] Innovation Tools[47:20] Evan’s proudest moment[49:40] Challenges for the future of machine learning[51:30] Get soft skillsResources:Evan’s LinkedIn: https://www.linkedin.com/in/eshellshear/Innovation Tools: https://amzn.to/2OrrAsjQuotes:“Take a step up and over to look at the problem in a new direction.”“It is in our human nature to overcomplicate things.”“I need to help the company understand what the true problem is.”“Take a low-risk approach to solve your client’s problem.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Rachel Fojtik is an Experienced Senior leader in Analytics, influencing change in behaviour, company culture, and improvement with analytics. Managing high performing teams that deliver across a myriad of knowledge areas. She is passionate about delivering information that sees results, using collaborative design and development. A demonstrated history of setting up teams that deliver end to end business intelligence implementations. Cross-industry experience in healthcare, telecommunications, the financial services industry, travel and tourism, and energy.Enjoy the show!We speak about:[01:15] How Rachel started in the data space[08:40] The motivation behind Rachel’s trailblazing[11:30] The metrics Rachel was helping optimize[14:10] Working with the management director vs. operational work[16:45] Data matching at Diner’s Club[22:15] Using a minimalist view[24:45] Find the best way – don’t just stick with what you know[28:45] If something is well presented, it is more likely to be trusted[35:00] What is a product manager?[42:50] An organic governance in the workplace[46:15] Rachel’s role as Director of Analytics and Performance[53:00] Building and working on a network[54:10] Do what you’re passionate aboutResources:Rachel’s LinkedIn: https://www.linkedin.com/in/rachel-fojtik-78321199/Quotes:“I created an input tool where a user could design the layout of their input form.”“I’ve always tried to go with a minimalist view.”“If your presentation is way too busy, it is difficult to take a story from that information.”“Consider where the eye goes first when creating a presentation.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Christoph Molnar is a data scientist and Ph.D. candidate in interpretable machine learning. He is interested in making the decisions from algorithms more understandable for humans. Christoph is passionate about using statistics and machine learning on data to make humans and machines smarter.Enjoy the show!We speak about:[02:10] How Christoph started in the data space[09:25] Understanding what a researcher needs[15:15] Skills learned from software engineers[16:00] Statistical consulting[19:50] Labeling data[23:00] Christoph is pursuing his Ph.D.[29:00] Why is interpretable machine learning needed now?[31:00] Learning interpretability[33:50] Accumulated local effects (ALE)[37:00] Example-based explanations[39:15] Deep learning[43:35] The illustrations in Interpretable Machine Learning.[49:50] How Christoph maximizes the impact of his timeResources:Christoph’s LinkedIn: https://www.linkedin.com/in/christoph-molnar-63777189/Christoph’s Website: https://christophm.github.ioInterpretable Machine Learning: https://christophm.github.io/interpretable-ml-book/Quotes:“Always look at the process when labeling data.”“After each chapter of my book, I publish it and get feedback.”“I randomly read a lot of papers and structure the knowledge to fit them together.”“I express what I want easier with illustrations in my book.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
Dr. Bülent Kiziltan is an AI executive and an accomplished scientist who uses artificial intelligence to create value in many business verticals and tackles diverse problems in disciplines ranging from the financial industry, healthcare, astrophysics, operations research, marketing, biology, engineering, hardware design, digital platforms, to art. He has worked at Harvard, NASA, and MIT in close collaboration with pioneers of their respective fields. In the past 15+ years, he has led data-driven efforts in R&D and built multifaceted strategies for the industry. He has been a data science leader at Harvard and the Head of Deep Learning at Aetna leading and mentoring more than 200 scientists.Enjoy the show!We speak about:[02:00] Bülent’s background[05:50] The transition from astrophysics to business[08:45] Data leaders need technical experience[12:45] Academics still need soft skills[19:20] What data science can offer organizations[23:50] Addressing causal inferences[25:30] Recommendations for implementing culture in the workplace[30:00] How a leader should balance priorities[36:10] Challenges Bülent currently faces in the industry[38:15] Hierarchy in the startup space[40:45] What Bülent loves about data science[42:45] Future data challengesResources:Bülent’s Website: http://www.kiziltan.org/Bülent’s LinkedIn: https://www.linkedin.com/in/bulentkiziltan/Quotes:“Culturally, I was surprised by the mindset of business leaders.”“We asked individual members of the data science group to come up with their own ideas that can be implemented in the day-to-day business operations.”“A diverse team is critically important for the business.”“All companies will become AI companies in one way or another.”Thank you to our sponsors:Fyrebox - Make Your Own Quiz!RMIT Online Master of Data Science Strategy and LeadershipGain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions.Visit online.rmit.edu.au for more informationAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!--- Send in a voice message: https://anchor.fm/datafuturology/message
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Comments (4)

Shane Wong

brilliant episode!!!

Aug 29th
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Balkan Misirli

Great podcast. The interviews are always insightful and the guests' recommendations have been really useful

Jul 29th
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Shane Wong

Best episode ever

Oct 17th
Reply

Saul Cruz

it'd be nice to have the three books you mentioned in the podcast's notes

Aug 15th
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