I am a data scientist and Bayesian methodologist with a PhD from The Ohio State University, specializing in generative modeling, behavioral economics, and software development. In my day role as Senior Manager of Data Science at Oscar Health, I lead a team focused on clinical risk adjustment for the ACA individual market. Across my career I have led teams to:

1. develop and deploy generative and ML models in production, from real-time Bayesian inference for digital therapeutics (Aivo Health) to state-space loss development models powering insurance-linked securities (Ledger Investing) and risk-adjustment models for the ACA individual market (Oscar);
2. design studies and publish 20+ peer-reviewed papers spanning computational psychiatry, mathematical psychology, and actuarial science, including methods work that has shaped how behavioral tasks are measured and modeled in clinical research; and
3. build internal and open-source tools—including hBayesDM (R/Python) and BayesBlend (Python), used by researchers and practitioners worldwide—that make day-to-day analytics work more delightful and less error-prone.

Through Bayesian Beginnings, my consulting practice, I help academic researchers and applied teams design, fit, and validate computational models—and build the reproducible pipelines that make the work last. With 20+ peer-reviewed publications and contributions to open-source software, I can be academic when rigor is needed, but also practical when it comes to tight deadlines and execution uncertainty.

TLDR; I have expertise in leading teams and building analytics tools across diverse industries. My skillset allows for me to make informed decisions even when faced with incomplete or uncertain data. I also really enjoy the work I do. Reach out if you are ever interested in chatting about it, or book a consulting engagement!

Download my CV.