Colman Humphrey is an engineer and data scientist with a PhD in Statistics and nine years of experience blending causal inference, machine learning, and statistical methodology into production-ready solutions. Based in New York, he has led teams and labs as a Data Science Principal at Via, founded and ran a startup as CEO of Slight, and now applies his quantitative skills at Neofactory. His background spans rigorous academic research to hands-on engineering roles including computational kinematics and geometry work, showing a rare comfort with both abstract theory and applied system design. Colman’s early analytic foundations include statistical modeling for ad platforms at Google and fraud analytics at EY, informing a pragmatic approach to modeling and visualization. He’s particularly interested in causal methods and data visualization, often turning complex statistical insights into actionable product features. Beyond titles, Colman brings an interdisciplinary curiosity—combining PhD-level statistics with geometric computation—that helps bridge research ideas and engineering execution.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Arts (BA) Mathematics, Bachelor of Arts (BA) Mathematics at Trinity College Dublin
Doctor of Philosophy (PhD) Statistics, Doctor of Philosophy (PhD) Statistics at The Wharton School
Small R package to run bootstrap methods on mixed models.
Contributions:2 releases, 52 commits, 12 PRs in 3 years 1 month
r-packagebootstrapmixed-models
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