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Data Futurology

Data Futurology

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
32 Episodes
#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: 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: 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: 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!
#28 Jennifer Prendki - VP of Machine Learning & Data Strategist
Jennifer started her career as a particle physicist before becoming a data scientist. After gaining experience in many fields including high frequency algorithmic trading & advertising, she was Atlassian's first Chief Data Scientist. Today she is the VP of Machine Learning at Figure Eight and an Expert and Advisor at the International Institute for Analytics.We speak about:* How to see the results of your work sooner and faster* The importance of choosing your manager* Making data strategy decisions for companies that are very immature in their approach to data* Building data science teams from scratch* Combining impostor syndrome and leaps of faith for your benefit* The importance of making mistakes to be successful* What having a great data culture really means* How to convince peers and supervisors on the benefits and the path of data strategy* Differences between having a technical and non-technical manager* Combining technical abilities and business sense* The importance of customer contact for technical people* Focus on the impact and outcome of everything that you're building* How to keep the balance in teams * Pleasing customers vs product intuition* How to drive and create a data driven culture* How to create scale with your data science efforts* How to build your data science team* Data engineering vs Machine learning engineer* How to keep talent* How can data scientists learn the skills for business leadership* Active learning and building products for data scientistsShow notes: Jennifer is based in Mountain View, CaliforniaAnd 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!
#25 Ben Taylor - Chief Al Officer & Cofounder
Ben started his career as a chemical engineer. He developed an interest for computer vision early on. He worked for Intel, then at a hedge fund and then became the Chief Data Scientist at HireVue. A couple of years ago he started his own AI startup called where he's is building a Deep Learning platform for product visionaries and software engineers.We speak about:* How computers amplify us* What it looks like to start your own AI company* How to switch programming languages* Downsides of Google's tensorflow* What industry expects from data science* How to deliver value with ML* How to pick ML projects to tackle* Eliminating bias in AI applications* AI powered job interviews of the (near) future* Topic discovery with DL* AI warfare in business* What is a Hive Mind and how it works* Future health care assessments at home* AI is cute until it's scary* The importance of passion and obsession in data scienceShow notes: Articles by Ben on Linkedin:This is Why Your Data Scientist Sucks: Al War Machine: Our Darkest Day Al War Machine: The Hive Mind That Data Science Job 0 to $100K+ data science job in 6 months is based in the Provo, Utah AreaAnd 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!
Comments (2)

Shane Wong

Best episode ever

Oct 17th

Saul Cruz

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

Aug 15th
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