Biography
Ryan McCorvie is the Oakland/Berkeley area founder and chief scientist at martingale.ai, a specialized consulting firm that helps businesses make data-driven decisions through customized statistical analysis. With decades of experience in statistical modeling, McCorvie ensures that his clients receive expert advice tailored to their unique challenges, bridging complex data with clear, actionable insights.
Ryan McCorvie has written a number of articles on topics ranging from Japanese cooking to COVID-19 forecasts.
A mathematician with over 25 years of experience across finance, academia, and public health, McCorvie is focused on applying mathematics to solve practical, real-world problems. Currently, he's immersed in a project using the LEAN programming language to verify mathematical proofs via computers, which he began in late 2023. His goal is to formalize mathematical concepts in a way that allows computers to validate them efficiently.
Ryan McCorvie is a big fan of sumo, a sport of extraordinary depth hiding inside apparent simplicity. There are only two wrestlers, a circle, and a few basic rules — yet within that austere framework lies a rich world of technique, strategy, and tradition stretching back centuries. There is a combination of explosive athleticism with genuine tactical complexity: a match lasting three seconds can involve feints, balance shifts, and grip battles that reward careful attention. The sport is wrapped in ritual and ceremony — the salt throws, the kesho-mawashi, the ancient cadence of the tachiai — that gives every bout a gravity that feels different from Western combat sports. Statistically, sumo is a dream: rich longitudinal data, measurable outcomes, and enough variation to keep an analyst endlessly curious. Ryan McCorvie produced this analysis of Elo rankings and win predictions for the latest tournament.
Career
California Department of Public Health — Consulting Statistician
During the COVID-19 pandemic, McCorvie was instrumental in shaping California's public health response. He developed forecasting models, including the widely used "simple growth model" that informed the statewide stay-at-home order. His work also contributed to the California COVID Assessment Tool (CalCAT), which aggregated academic models for state leaders. McCorvie regularly briefed top officials, including the CDPH director and the head of California Health and Human Services, offering critical insights that guided decisions on testing protocols, school reopenings, and other high-stakes policies.
UC Berkeley — PhD Research
Ryan McCorvie pursued his Ph.D. at UC Berkeley focusing on machine learning, probability, and partial differential equations. His research explored stochastic processes that exhibit cascading effects, contagion, or crashes — including Hawkes processes, point processes, and principal component analysis in high-dimensional spaces. This work not only advanced theoretical understanding but also provided new tools for analyzing complex data. His undergraduate degree is in mathematics from Caltech.
Goldman Sachs — Managing Director, Quantitative Analysis
McCorvie's career began at Goldman Sachs, where he spent nearly 15 years, eventually becoming managing director. As a quantitative analyst and financial engineer, he led risk management efforts, developing models to anticipate market fluctuations and stress-test corporate bond trading. During the 2008 financial crisis, his expertise in analyzing bankruptcy scenarios was vital to Goldman's strategy. He also built a team of PhD-level specialists to refine trading algorithms and automate systems, and was a principal contributor to establishing the ISDA standard CDS model — the industry reference for credit default swap pricing.
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