Lenny Bronner

I run Broome Street Labs, a data practice focused on election data, forecasting, and beyond. Before founding it, I spent nearly ten years at The Washington Post, working on elections, media, and the messy real-world data that both produce. Most of my career has been spent building statistical systems that have to work in public, under deadline, and often on incomplete data.

My work has mostly fallen into a few areas:

• Election data and modeling. Live forecasting from partial returns, polling averages, voter registration data, and estimating how different groups actually voted. At The Washington Post, I built their first live election night model and later led the team that rebuilt it.
• Data infrastructure for newsrooms. Pipelines and tools that let journalists work with voter files, campaign finance filings, and other public data without needing a data scientist in the room. Some of that work contributed to reporting that won the 2022 Pulitzer Prize for Public Service.
• Personalization and online learning. Recommendation, metadata tagging, and production bandit systems for deciding what to show readers and when, including push notifications and recirculation.
• Explaining any of the above. I’ve written about our methods, presented them at conferences, and gone on live television to explain a forecast while it was running.

I have an M.Sc in Statistics and a B.Sc in Mathematical and Computational Science, both from Stanford.

My CV has the full detail — roles, methods, publications, and talks.

For project inquiries, reach out through Broome Street Labs. For speaking, press, or anything else, email me at lenny.bronner@gmail.com.