The goal of this track is to share best practices about everyday data science from top practitioners. It features talks that cover common challenges facing data science teams and ICs – while reminding us of the tremendous power of data, analytics and ML applied in a business context. Come and learn from each other's hard lessons and avoid common pitfalls.
This track is for the everyday data scientist, or engineers wanting to learn more about what data science is all about. Talks will obviously get into technical detail, but will also be of interest to product managers wanting to understand how to do more to integrate data science into their product development process.
Jim Savage is a Manager, Data Science at Schmidt Futures, where he assists portfolio projects in prototyping their data science solutions, and helps to source grant and investment opportunities. Before Schmidt Futures, Jim was Head of Data Science at Lendable, where he built systems to automate due diligence processes and price portfolios of small loans in Sub-Saharan Africa. He also worked at the Grattan Institute in Australia, where he worked primarily on retirement savings policy, and at the Australian Treasury, on the ill-fated 2011 carbon price. He is a Bayesian statistician who specializes in discrete choice, causal inference, time series analysis, and the incorporation of contemporary machine-learning methods into all three fields.
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