Michael Senter is a Senior Research Statistician Developer with a PhD in Applied Mathematics and 12 years of experience building production-grade statistical software at SAS, specializing in missing data methodology and causal inference. He designs and ships novel algorithms in C/C++ for SAS Viya, having delivered pioneering features like the PROC MI FLUX option and tackled longstanding problems such as optimal variable ordering for monotone missingness. Equally at home in research and engineering, he bridges the gap between theory and product by authoring performant core routines, supervising complex migrations with zero regressions, and publishing applied work in epidemiology and mathematics. A pragmatic DevOps modernizer, he pioneered GitHub Actions, CI testing strategies, and BDD-style unit testing that let Python testers exercise C-level logic, and he’s the team expert on GitHub Copilot and AI-assisted development. Not obvious from his title: he routinely uncovers silent data-corruption issues and performance bugs under production pressure, and has a track record of shipping fixes that improve accuracy and speed for regulatory submissions. Based in Cary, NC, he combines deep statistical insight with software craftsmanship to deliver reliable analytics for clinical and life-science applications.
12 years of coding experience
6 years of employment as a software developer
The University of Utah
Doctor of Philosophy (Ph.D.), Applied Mathematics, Doctor of Philosophy (Ph.D.), Applied Mathematics at The University of North Carolina at Chapel Hill
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Michael Senter - Senior Research Statistician Developer