Nick Chamandy is the Head of Data Science at Lyft. Before joining Lyft, he learned his trade as a member of the Ads Quality Team at Google. Nick got his PhD in Statistics from McGill University, where he studied brain imaging applications under the supervision of Keith Worsley and Russ Steele. Currently, Nick's work centers around travel time prediction, dynamic pricing, and experimentation. He is fascinated by new data science problems, and driven by the prospect of building better products, and sharing deeper insights, with data.
After receiving his PhD in physics at Yale University, Jonathan worked as a researcher studying phase transitions in the very early universe. His academic work focused on developing theoretical and computational tools to understand the statistical properties of very hot, strongly interacting matter. After leaving academia, Jonathan worked in scientific publishing as an assistant editor for the Physical Review, a leading physics journal.
Prior to joining PlaceIQ, Jonathan spent several years in the quantitative trading industry where he applied large-scale optimization and machine learning techniques to tick-level equity pricing data and developed several real-time trading algorithms and analytics platforms. Jonathan brings a wide-rage of computational and mathematical skills to PlaceIQ as well as a passion for machine learning, visualization and building large data analysis pipelines.
Josh Schwartz is Head of Product Engineering and Data Science at Chartbeat, where he develops infrastructure and algorithms for Chartbeat's new generation of products. In a prior life, he researched machine learning, optimization, and computer vision at MIT, Cornell, and the University of Chicago.
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