Jonathan Gellar is a Senior Statistician at Mathematica with 11 years of experience leading statistical design and analysis for evaluations in healthcare policy, education, child welfare, and financial inclusion. He combines PhD-level biostatistics and an MPH from Johns Hopkins with deep methodological breadth in causal inference, predictive modeling, and survey analysis using both Bayesian and frequentist approaches. At Mathematica he directs all statistical aspects of projects, translating complex policy questions into rigorous study designs and actionable findings. His background includes algorithm development for multi-contrast MRI segmentation and hands-on research roles across academic and clinical settings, reflecting a blend of computational, clinical, and policy expertise. Known for bridging technical rigor and real-world impact, he brings a pragmatic focus on reproducible, policy-relevant inference.
11 years of coding experience
13 years of employment as a software developer
Bachelor of Science (BS), Biomedical/Mechanical Engineering and Computer Science, Bachelor of Science (BS), Biomedical/Mechanical Engineering and Computer Science at University of Southern California
Doctor of Philosophy (PhD), Biostatistics, Doctor of Philosophy (PhD), Biostatistics at Johns Hopkins Bloomberg School of Public Health
Contributions:113 commits, 98 pushes, 4 branches in 1 year 1 month
regressionfunctional-data
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