Lenny Bronner
Data Science Lead, Election Insights
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolLenny Bronner is a data science lead at The Washington Post who designs and operates the newsroom’s live election forecasting model, translating complex probabilistic outputs into actionable journalism. With 11 years of experience and an MS in Statistics from Stanford, he combines rigorous statistical modeling and machine learning with product-minded tooling for reporters. He progressed through senior technical roles at The Post after earlier data science work at Sidewire, demonstrating both individual contributor depth and team leadership. Originally from Vienna and now based in New York, Lenny brings a journalist-centered approach to production analytics, prioritizing explainability and real-time reliability in high-stakes coverage.
11 years of coding experience
7 years of employment as a software developer
Master of Science (MS) Statistics, Master of Science (MS) Statistics at Stanford University
English, German
Github Skills (38)
twitter-api9
twitter8
elections7
parser6
python6
csv-parser6
csv-reader5
csv-parsing5
parse5
transparency5
finance5
json4
restful-api4
nodejs4
api4
Programming languages (5)
Github contributions (5)
washingtonpost/elex-live-model
Sep 2022 - Jan 2023
a model to generate estimates of the number of outstanding votes on an election night based on the current results of the race
Contributions:1 release, 213 reviews, 55 commits in 3 months
votesnightelectionraceestimates
washingtonpost/2020-election-night-model
Oct 2020 - Jan 2021
2020-election-night-model
Contributions:1 review, 17 commits, 7 PRs in 2 months
electionnight
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