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Speaker "Michael Li" Details Back

 

Topic

Data-Driven Hiring of Data Scientists

Abstract

Hiring -- even for data scientists -- is often not very data driven. At The Data Incubator, we run a fellowship to train and place data scientists in various industries that regularly receives over 2000 applications per session. To cope, we have to rely on robust analytics and machine-learning for our admissions process to ensure we are finding the best talent for our hiring partner companies. We’ll explain why most traditional keyword-driven screening processes do not work for finding data science talent and how to both streamline and build an automated data-driven screening process that filters for skills and talent, not keywords and hype.

Profile

Michael Li founded the Data Incubator (http://www.thedataincubator.com), a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to fellows, and routinely accepts just 1% of applicants. Employers engage with the Incubator as hiring partners. Previously, he worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves. Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events. You can find out more at http://www.thedataincubator.com or @thedatainc.