Sheridan Grant is a Principal Research Scientist with 11 years of experience applying causal inference, econometrics, and machine learning to real-world social and economic problems. Currently at Ozette after impactful roles at Zillow, Sheridan has modeled housing economics, led algorithmic fairness analyses, and built fast, trustworthy experimentation systems. Their PhD work focused on causal approaches to fairness in peer review, bridging rigorous theory with applied evaluation on election and review data. Comfortable moving between Bayesian methods, high-dimensional testing, and scalable computational pipelines, Sheridan has also contributed to genomics, energy market modeling, and even algebraic geometry—showing a willingness to tackle technically diverse domains. Based in Seattle, they combine deep statistical expertise with practical product-minded delivery, often surfacing subtle causal questions that standard ML approaches miss.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Statistics, Doctor of Philosophy - PhD Statistics at University of Washington
Bachelor of Arts (B.A.) Mathematics and Statistics, Bachelor of Arts (B.A.) Mathematics and Statistics at Pomona College
High School Diploma, High School Diploma at Huntsville High School
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