I'm a data scientist who builds the full stack of a data product — from the probabilistic model at its core to the app that ships it. Over 10 years at fast-moving companies I've built production ML and forecasting systems, run large-scale experiments, and turned messy data into decisions. Lately I work where Bayesian modeling, LLM and agent tooling, and full-stack engineering meet: PyMC models that sample in the cloud, MCP servers that give AI agents real capabilities, and interactive apps built with React, Next.js, and Rust/WebAssembly.
Companies I've Worked With
What I Work On
Bayesian & probabilistic modeling
Design and fit models for inference, forecasting, and decisions under uncertainty.
Production ML & forecasting at scale
Build forecasting and ML systems that run in production — plus the experimentation frameworks to measure them.
LLM & AI engineering
Build agentic tooling and MCP servers, integrate the Claude API, and ground outputs with evals and citations.
Full-stack data products
Ship end-to-end: data pipelines, APIs, and interactive front-ends — then deploy and self-host them.
Education
Master of Science in Artificial Intelligence
University of San Francisco
Bachelor's in Neuroscience
Rice University
Recent Adventures
Tamanawas Falls
Parkdale, Oregon
Forest Park
Portland, Oregon
Water and Lava
Sisters-Millican, Oregon