#29 Dr. Klaus Ifflander - Chief Analytics Officer

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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.life

We 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 startups

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

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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 scientists

Jennifer is based in Mountain View, California

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!

#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!