About Me

Hi, I’m Dan, a developer advocate at Databricks focused on Generative AI. I make MLflow guides and examples, build AI agent demos on Databricks, and help with technical events, etc.

This site is where I publish first. Expect regular posts on LLMs, open tooling, and the day-to-day craft of building with Databricks.

Before Databricks, I worked at bit.io, a fast, developer-friendly hosted Postgres. I used it to manage data for research and writing projects, covering topics like methane emissions, Bayesian statistics, labor turnover, and U.S. House representation.

Earlier, I was Director of Data Analytics at the Guinn Center for Policy Priorities in Las Vegas, where I led data-driven policy analysis across public health, climate, and the 2020 Census.

I studied History of Science (B.A., University of Chicago) and Statistics (M.S., University of Minnesota). My graduate work compared tests for heterogeneity of risk difference across patient subgroups in clinical trials. In 2018, I was a graduate research fellow in the Data Science for the Public Good program at the Biocomplexity Institute of Virginia Tech. I’ve also taken on consulting projects for nonprofits and companies.