I'm a data scientist who loves building scalable data products.

I love data and helping companies understand consumer behavior at scale. My path started in Psychology and Statistics, which pulled me into consumer and marketing problems: why people choose what they choose, and how that shows up in the numbers. Working inside fast-moving startups and consumer-tech teams sharpened the engineering side, and gave me the mindset to build data products that real users actually rely on.

My current focus is AI agent systems: applications where LLMs are grounded in real tools, real data, and real decisions. The two projects at the top of this site are working examples: a multi-agent customer segmentation pipeline, and a hybrid embeddings and LLM workflow for coding open-ended survey responses.

Before LLMs were the default, I spent years writing Python, R, and BigQuery, building Looker and Tableau dashboards, and shipping ML at scale.

I'm open to senior data science and applied AI roles, ideally with mission-oriented companies solving problems that affect millions of people.