#27 Dr. Mark Nasila - Chief Analytics Officer

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Mark used to be a statistics lecturer at Nelson Mandela University in South Africa. He then joined First National Bank as a quantitative analyst where he climbed through the ranks to Head of Advanced Analytics and beyond. Today he is the Chief Analytics Officer at FNB.

We speak about:

* Predicting what the customer is calling about

* Improving compliance in banking through analytics

* Creating and driving a data strategy across an organisation

* Using analytics to look after customers in better ways

* How to create and measure economic value from data

* How to find meaning in your work

* Understanding your value across the entire value chain

* Creating a culture of collaboration that's not afraid to fail

* Working with tertiary institutions to identify talent

* What to test when interviewing data scientists

* How to structure your team & work with stakeholders

* The importance of data governance

* How to implement and socialise the solutions created by the team for maximum impact

* The importance of mentoring and growing people

* The difference between head of analytics and chief analytical officer

Mark is based in the Johannesburg Area, South Africa

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!

#26 Sam Robertson - Head of Research & Innovation

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Sam's background is in sports & exercise science. He has an accomplished career in sport analytics. Today, he is the Head of Research and Innovation at the Western Bulldogs and an Associate Professor at Victoria University.

We speak about:

* Using ML to help people see the non-linerarity in their problems

* Common misconceptions of ML

* Interpretability of ML

* Using ML to improve athletes performance, measure their contribution & prevent injuries

* Carving a data science job in an area you're interested in

* How to choose projects to focus on

* Mixing psychology, operations and data science in sport

* Data collection & management in sport

* How data can help off field & the mental side of the athletes

* Similarities of data in sport and government/ corporate

* How athletes change when fatigued

* Applications of sports analytics

* How data can help create drills to improve player performance & skills

* Current modelling challenges in sport

* Real time decision making in game by coaches: challenges and realities

* Educating stakeholders


Sam is based in Melbourne, Australia

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!

#25 Ben Taylor - Chief Al Officer & Cofounder

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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 Ziff.ai 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 science

Articles by Ben on Linkedin:

This is Why Your Data Scientist Sucks:

https://www.linkedin.com/pulse/why-your-data-scientist-sucks-benjamin

The Al War Machine: Our Darkest Day

https://www.linkedin.com/pulse/ai-war-machine-our-darkest-day-ben-taylor-deeplearning-/

The Al War Machine: The Hive Mind

https://www.linkedin.com/pulse/ai-war-machine-hive-mind-ben-taylor-deeplearning-

Getting That Data Science Job

https://www.linkedin.com/pulse/getting-data-science-job-ben-taylor-deeplearning-/

From 0 to $100K+ data science job in 6 months

https://www.linkedin.com/pulse/from-0-100k-data-science-job-6-months-ben-taylor-ai-hacker/

Ben is based in the Provo, Utah Area

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!

#24 Mistakes in Building a DS Capability by Felipe Flores

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This is a different type of episode! This episode is a presentation I recently did at a large financial services institution. I presented on 5 Mistakes and Lessons Learned in Driving Business Value with Data Science and the Cloud.

I talk about:
- Using Lean Startup and Design Thinking principles in Data Science
- The importance of staying close to your end customer and what that looks like in practice
- The difference between machine learning for machines and for humans
- What is the purpose of ML/AI and how you can bring that thinking into your organisation
- What using ML for humans looks like
- Using data from other areas
- Leverage the flexibility of the cloud

Questions:

How can I learn data science?

Online Courses:

  • John Hopkins Data Science Specialisation on Coursera

  • Machine Learning by Andrew Ng on Coursera

  • Springboard: online course with mentor - get $250 off http://bit.ly/df-sb


Slides below. 

Felipe is based in Melbourne, Australia

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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#23 Mario Vinasco - Marketing Analytics and Data Science Manager

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Mario is an Electrical Engineer from Colombia. He went to Silicon Valley to do his Masters at Stanford University and stayed to build a career in Marketing Analytics. He has incredible experience and has worked at Intuit, Google, HP, Symantec and Facebook. He currently works at Uber as Marketing Analytics and Data Science Manager.

We speak about:

  • Starting in marketing analytics without knowing anything about it

  • The creatives and the quants of marketing analytics

  • How the headaches of tech have changes over the years for data scientists

  • Data dictators and why multiple versions of the truth are necessary

  • How to communicate results of your analysis to executives

  • The importance of data science education in organisations

  • How to pick the best predictive model for your applications

  • Analytics as the art of counting

  • The importance of working with inspiring people

  • Why running experiments is the gold standard of finding what works

  • How to use people analytics - Google style

  • Why your job is to empower your stakeholders - and how to make this a 2 way relationship

  • How to not saturate your channels

  • What he looks for in CVs and applicants

  • How to stand out during interview processes

  • The coolness of network partitions at Facebook

  • Using embeddedings at Facebook - using vectors when one hot encoding gets too cumbersome

  • The importance of rapid prototyping

  • The value of collaboration across your organisation and what that looks like in practice

  • Things to look for and ask during your interview process

  • How to choose where to work

  • Setting up new practice globally at Uber

  • Product manager as a facilitator, protector and enabler



Mario is based in the San Francisco Bay Area

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!