Michael Guo is a Senior Applied Scientist at Uber in New York with five years of industry experience applying ML to personalization, targeting, and time series forecasting. He progressed from time series roles into personalization work after earlier positions at Aetna/CVS and C2FO where he focused on causal inference and forecasting for business impact. His background includes a MS in Financial Engineering and Mathematics and a publication from research at Los Alamos National Laboratory, reflecting a blend of rigorous quantitative training and production ML. Known for turning complex temporal and causal problems into scalable systems, he brings both research credibility and hands-on product delivery to high-impact personalization pipelines.
5 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BS) Mathematics, Bachelor of Science (BS) Mathematics at South China Agricultural University
Master of Science (MS) Financial Engineering; Mathematics, Master of Science (MS) Financial Engineering; Mathematics at Claremont Graduate University
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