Noah Greifer is a statistical consultant and R package author at Harvard’s Institute for Quantitative Social Science with nine years of experience applying causal inference methods to problems in health and the social sciences. He develops and maintains widely used R tools—such as WeightIt, MatchIt, and cobalt—that implement propensity score matching, inverse probability weighting, and balance assessment, and frequently collaborates with substantive and methodological researchers. His PhD in Psychometrics and Quantitative Psychology underpins a rigorous blend of regression, machine learning, and optimization in his software and research. Active in public Q&A forums and GitHub issue threads, he channels community feedback into package improvements and reproducible workflows. Based in New York, he prefers technical discussion via GitHub, CrossValidated, or StackOverflow rather than LinkedIn, reflecting a strong open-source and community-driven support posture.
9 years of coding experience
7 years of employment as a software developer
University of California, San Diego
Doctor of Philosophy (PhD), Psychometrics and Quantitative Psychology, Doctor of Philosophy (PhD), Psychometrics and Quantitative Psychology at University of North Carolina at Chapel Hill
Contributions:178 commits, 52 pushes, 1 branch in 4 years 4 months
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