Summary
Jerome Thai is a Senior Staff Data Scientist with 13 years of experience building end-to-end ML and optimization systems that scale across hyper-growth marketplaces. He has driven measurable business impact—architecting real-time pricing and reinforcement learning frameworks at Lyft that protected tens of millions in revenue and now leading Transformer-based forecasting for 1M+ SMBs at Parafin processing over a billion daily sales points. Jerome blends deep academic rigor (PhD-level EECS work and operations research training) with product-focused engineering, shipping automated training, inference, monitoring, and portfolio simulation platforms used to set executive risk posture. He’s comfortable moving research prototypes into P0 production priorities—evidenced by a hackathon-winning attention-based forecasting model that became core roadmap work—and often operates at the intersection of causal ML, quantile risk modeling, and large-scale systems engineering. Based in the San Francisco Bay Area, he pairs strong mathematical foundations with practical system-building to optimize marketplace efficiency under real-world constraints.
14 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.), EECS - Minor in Statistics, Doctor of Philosophy (Ph.D.), EECS - Minor in Statistics at University of California, Berkeley
Master of Engineering - MEng, Operations Research, Applied Mathematics, Master of Engineering - MEng, Operations Research, Applied Mathematics at École Polytechnique
Master of Science (MS), Operations Research, Master of Science (MS), Operations Research at Columbia Engineering
French, English