DiscoverData Futurology - Data Science, Machine Learning & Artificial Intelligence From Top Industry Leaders
Data Futurology - Data Science, Machine Learning & Artificial Intelligence From Top Industry Leaders
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Data Futurology - Data Science, Machine Learning & Artificial Intelligence From Top Industry Leaders

Author: Felipe Flores

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Data Futurology is data 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
38 Episodes
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How to build a world class data science team
In this episode, I talk about data scientists and ways you can attract the best talent to your team. Instead of telling your employees what they can do better, make them curious as to what they could do better. Then, I reveal the three things to look for when analyzing your pool of applicants. Once you have your team, now what? Once you have a decent pay settled, I explain the three things you will need to have for a capable team. Later, I tell you the elements, as a manager, you should be doing as rarely as possible.In This Episode:• [02:45] How to attract data scientists to your team?• [04:45] The three things to look for from your pool of applicants• [07:05] Adversity; test how they would react • [11:00] Three things needed to run an effective team• [18:00] Managers should be doing this as rarely as possibleCreating a Data Team Session Quotes:1. “Create a learning environment and continually challenging projects to focus on their development.”2. “People should be open-minded and willing to learn; I test this in two different ways.”3. “A lot of people come with technical skills from other countries.”4. “They had to code it live with about eight people watching them, no pressure!”5. “You know the answer, and you want to tell them to get to the outcome quickly. That’s an urge you have to roll back and fight against.” 6. “Purpose is really what gets us out of bed every day.”7. “Make yourself redundant as quickly as possible.”Resources Mentioned: Drive: The Surprising Truth About What Motivates UsConnect:Twitter - https://twitter.com/datafuturologyInstagram - https://www.instagram.com/datafuturology/Facebook - https://www.facebook.com/datafuturologySupport Data Futurology on Patreon! https://www.patreon.com/datafuturologyThank you to our sponsors:JCU Master of Data Science - Online ProgramFyrebox - Make Your Own Quiz And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
Dr. Kristen Sosulski - Associate Professor of Data Visualization NYU Stern; Director, Learning Science Lab; Author of Data Visualization Made Simple and Consultant
In this episode I talk to Kristen Sosulski who is the Data Visualization Professor at NYU Stern School of Business. She has just written the book Data Visualization Made Simple: Insights Into Becoming Visual. An interest in using technology to help students learn has led to helping people to understand how to use data visualizations to communicate insights to others.Kristen and I discuss guidelines on creating data visualizations, why presenting data visualizations is as important as creating them, and how the software needs to improve. Dr Kristen Sosulski is an Associate Professor of Information Systems at New York University’s Stern School of Business. She teaches MBA, undergraduate, executive, and online courses in data visualization and computer programming. She is also the Director of the Learning Science Lab for the NYU Stern where she leads teams in design immersive learning environments for professional business school education. Summary• Kristen’s journey from doing her undergraduate in Information Systems at NYU Stern School of Business to being a professor there teaching Data Visualization (00:17)• How Kristen’s love of technology led to an interest in using technology to help students learn (01:38)• The challenges of trying to create an immersive learning environment in the late 90s (02:41)• What led to Kristen working with data visualization (03:38)• How Kristen thinks about data visualization and designing data graphics (06:14)• Some guidelines and thoughts on presenting data to an audience (08:03)• How people learn to improve their data graphics (11:15)• The importance of showing your work and getting feedback (14:18)• The challenges Kristen finds when consulting for companies in data visualisation (17:08)• The value of data visualization in a data driven organisation (19:54)• Why Kristen wrote her book on data visualization and why she included case studies (21:14)• Some resources that Kristen created for the book (23:40)• Her work in building NYU’s online education and the use of learning analytics (27:11)• Why there needs to be more training in how to visualize data and to understand what it means (30:10)• Designing a dashboard for user driven storytelling (33:41)• How Kristen would like data visualization to evolve in the future (36:44)• Mistakes people make when creating visualizations (38:51)• How Kristen developed and improves her work and the value of sharing your mistakes (41:33)• The importance of understanding what your data means in the real world (42:49)LinksData Visualization Made Simple: Insights into Becoming Visual by Kristen Sosulskihttps://www.amazon.com/Data-Visualization-Made-Simple-Insights/dp1138503916The Online Certificate in Visualizing DataTaught by Kristen Sosulski via NYU Stern School of Businesshttps://www.stern.nyu.edu/programs-admissions/online-certificate-courses/visualizing-dataSupport Data Futurology on Patreon! https://www.patreon.com/datafuturologyThank you to our sponsors:JCU Master of Data Science - Online ProgramFyrebox - Make Your Own Quiz
#32 Carole Wai Hai - Head of Data Science & Analytics
Carole had an unusual path into data science. She's worked as a content project manager, in strategic planning and in sales before getting into data through Business Intelligence at Fyber where she eventually became their Head of Analytics. Today she is the Head of Data Science & Analytics at Tenjin.We speak about:* The strengths of being a generalist* Upskilling throughout your career* Focus on self service reporting* The skills needed in a BI team* Creating internal user groups to share knowledge* Convincing people to get training on the tools required to do their job better* The benefits of gaining a reputation internally* Setting a strategy for data teams* The importance of data modelling skills in data teams* Learning technology on the job when you're background is not technology* Monthly meeting with key departments to review all dashboards in the department* Working remotely in global companies* Metrics about user behaviour* Offering analytics for many customers with the same problem/need* How to develop consulting skills* The platinum rule - book on communication style* The leadership challenge - book recommendation* What it's like working in startups* How to recover from being a workaholicShow notes: www.datafuturology.com/podcast/32Carole is based in Berlin Area, GermanyAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
#31 Scott Wilson - Founder & CEO
Scott started his career pushing trolleys at Woolworths. In his career he rose to management levels in retail with Woolworths, consumer goods with Kraft Foods, Fonterra SPC and PZ Cussons, then in media with 21st Century Fox. He then became the CEO of iSelect, a role he left earlier this year to start his own AI company Wilson AI. We speak about:* Focus on customer needs* Digitising industries to access more data* Helping companies in multiple industries to begin their data analytics journey* How to differentiate your company when competitors have access to the same data* How to overcome being "data rich but insight poor"* Changing industry power dynamics through data* Creating new teams to create value from data* The importance of storytelling in data science* Defining objectives with your data analytics communication* Educating industries to use data more effectively* Understanding costs & priorities across the value chain to make better decisions* Eliminating your biases when dealing with customers* Process re-engineering & AI* How to think outside of the building* How to start an AI company* The importance of translating between business and technical* How to connect data science and the boardroom* The importance of data science education in an organisations journey* How to achieve a wider spread adoption of AI* Focusing on cost & revenue with data science for maximum impact* Resist the urge to boil the ocean* The role of a CEO in a publicly listed company* Focusing on the top 3 business priorities* Productionising AI & monitoring unintended consequencesShow notes: www.datafuturology.com/podcast/31Scott is based in Sandringham, Victoria, AustraliaAnd as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
#29 Dr. Klaus Ifflander - Chief Analytics Officer
Klaus started his career doing internships at Yahoo! and the port of Hamburg. He worked as a consultant and completed a PhD in Quantitative Marketing. Today he is the Chief Analytics Officer at YAS.lifeWe speak about:* The importance of getting applied experience as early as possible* Defining KPIs for businesses* Using data to change organisational behaviour and increase safety* How to navigate organisations to create data definitions* Realities of consulting: positives and negatives* Why large companies require so much custom work* How to help people and organisations that don't know what they want* Helping organisations in progressing through their analytics journey* How to overcome technical challenges with creative solutions in your projects* Why honesty within yourself and others is imperative in your work* How to provide customers what they need instead of what they want* The importance of hard and soft metrics when measuring value* Applying soft skills in data science* How to find what will be valuable for your customers* Expanding your interest with a postgraduate degree* How your social surroundings affect your purchase decisions* Using soft skills for data acquisition* What is eigenvector centrality and what is it used for?* How product reviews influence your buying decisions* How to create experiments in business* Pricing models in the steel business* Data science in fitness startupsShow notes: www.datafuturology.com/podcast/29 Klaus is based in the Berlin Area, Germany.And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
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Comments (2)

Shane Wong

Best episode ever

Oct 17th
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Saul Cruz

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

Aug 15th
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