Kevin Fry
Quantitative Researcher
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolKevin Fry is a quantitative researcher with eight years of experience translating statistical theory into production-grade inference methods and high-frequency trading strategies from Palo Alto. With a Stanford PhD in Statistics and an MS in Computer Science, he has developed novel selective inference procedures applied to public-health and genomics datasets and now applies those skills to systematic delta-one strategies at DRW. His background spans academic research, industrial AI labs, and hands-on consulting—building validation pipelines for spatial subsurface models and stat-arb alpha generation for equities. Kevin combines rigorous probabilistic thinking with software engineering to ship open-source tools that make advanced inference practical, and he often bridges domain gaps (e.g., applying lasso-based selective inference to CDC flu forecasting and Crohn’s genomic studies).
8 years of coding experience
4 years of employment as a software developer
High School, High School at Arcadia High SchoolPhD, Statistics, PhD, Statistics at Stanford University
Github Skills (9)
r-package9
probabilistic7
prediction7
graphical-models7
probabilistic-graphical-models6
python5
inference5
machine-learning5
structured-data3
Programming languages (3)
Github contributions (5)
kevinbfry/scikit-learn
Jun 2022 - Jan 2024
Modifying scikit-learn to do added noise bootstrapping
Contributions:1 review, 4 PRs, 5 pushes in 1 year 7 months
pythonbootstrappingto-domachine-learningscikit-learn
kevinbfry/selective-inference
Aug 2018 - May 2024
Software for selective inference
Contributions:2 PRs, 16 pushes, 2 branches in 5 years 9 months
pythonldaselectiveinferencemachine-learning
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