Data Science & Machine Learning, Statistics, Bayesian methods, spatiotemporal modeling, and making complex quantitative work accessible.
I build predictive models, operationalize complex algorithms, and bridge quantitative science with policy and data-driven decision-making.
In the News
Selected through a national competitive process to bring statistical modeling and data science expertise to weather, water, and climate decision-making at the AMS Policy Program.
All news coverage →R (Rcpp, Shiny, tidyverse) • Python (NumPy, Pandas, scikit-learn) • C++ • SQL • Git • High-Performance Computing (Slurm)
Bayesian Inference • MCMC Algorithms • Spatiotemporal Modeling • Time Series Forecasting • Mixed-Effects Models • Missing Data Imputation
ETL Pipelines • Geospatial Data (ArcGIS Pro, GDAL) • API Integration • Data Quality Control • Reproducible Workflows
Scientific Writing • Presenting to Non-Experts • Mentorship • Team Collaboration • Accessibility in Quantitative Work