Samuel Thomas
Senior Director, US Reinsurance Catastrophe Analytics
Westfield, Indiana, United States
Summary
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Senior🎓
Top SchoolSamuel Thomas is a data scientist, accredited actuary, and Head of Process Automation with nearly two decades of experience applying Bayesian statistics and scalable engineering to finance, insurance, and government analytics. He leads global automation and cloud data infrastructure initiatives—architecting Databricks/Unity Catalog deployments and AI-enabled tools—to replace legacy Excel workflows and drive reproducible analytics across US/UK teams. His work spans catastrophe and cyber-risk modeling, where he has shaved model runtimes from hours to minutes using parallelism and vectorized computation, and created polynomial-time Bayesian algorithms for production use. A PhD in Biostatistics and published author on Hamiltonian Monte Carlo, he combines deep statistical theory with hands-on software skills in R, Python, C++, SQL, and Azure Databricks. Samuel has a track record of translating complex, multi-source data into executive-ready dashboards and approved models (including a federal GSA allocation and contracting spend model) and contributes open-source R packages used in forecasting and Bayesian GAMs. Based in Westfield, Indiana, he balances technical leadership with practical delivery, often surfacing novel NLP and clustering solutions to extract operational insights from messy text and scripts.
9 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Biostatistics, Doctor of Philosophy (Ph.D.) Biostatistics at Indiana University IndianapolisM.S. Mathematics, M.S. Mathematics at Purdue UniversityB.S.E.E. Electrical Engineering, B.S.E.E. Electrical Engineering at University of Notre DameProgramming languages (2)
Github contributions (5)
sthomas522/hmclearn
Sep 2019 - Oct 2020
Contributions:1 release, 279 commits, 98 pushes in 1 year
sthomas522/bayesGAM
Sep 2020 - Mar 2022
Contributions:56 commits, 44 pushes, 1 branch in 1 year 5 months
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