Chris Dobronyi is a Senior Data Scientist - Research at Google with a PhD in Economics from the University of Toronto and a decade of experience bridging econometric theory and applied data science. He previously taught computational economics at the University of Chicago and coordinated TA training at U of T, demonstrating a strong commitment to pedagogy alongside research. His academic work centers on non-parametric identification, informing robust, assumption-light approaches to causal inference and model design in production settings. At Google he progressed from Data Scientist to Senior Data Scientist, translating advanced statistical methods into scalable research products. Based in New York, he blends rigorous economic theory with practical engineering to tackle complex measurement problems. Colleagues describe him as someone who moves comfortably between formal proofs and hands-on implementation, making theoretical insights operational.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Economics, Doctor of Philosophy - PhD Economics at University of Toronto
Bachelor of Arts - BA Economics, Bachelor of Arts - BA Economics at York University
Contributions:10 pushes, 1 branch in 6 years 4 months
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