Brian Dumbacher
Mathematical Statistician
Washington, District of Columbia, United States
Summary
👤
Senior🎓
Top SchoolBrian Dumbacher is a mathematical statistician with nine years of experience at the U.S. Census Bureau, where he researches Big Data and machine learning methods to enhance the detail, quality, and timeliness of economic data products. He currently serves on the Emerging Methods Staff in the Economic Directorate, having previously designed samples and estimators for demographic and public-sector surveys. Brian pursues rigorous academic work alongside applied research, completing an MS at Stanford and undertaking a part-time PhD in statistics at The George Washington University focused on robust Bayesian small area estimation. He presents work to venues such as the Joint Statistical Meetings and the Federal Committee on Statistical Methodology Research Conference, translating advanced methodology into operational survey improvements. Comfortable at the intersection of math, code, and geography, he combines theoretical depth with practical implementation to tackle real-world data challenges. Colleagues find him curious and persistent—equally at home prototyping novel algorithms and shepherding them toward production use.
9 years of coding experience
Bachelor of Science (B.S.), Mathematics, Bachelor of Science (B.S.), Mathematics at University of Southern CaliforniaDoctor of Philosophy (PhD), Statistics, Doctor of Philosophy (PhD), Statistics at The George Washington UniversityMaster of Science (M.S.), Statistics, Master of Science (M.S.), Statistics at Stanford University
English, German
Github Skills (5)
machine-learning10
python10
text-classification10
natural-language-processing5
classification5
Programming languages (1)
Github contributions (5)
brian-dumbacher/treasure-hunt
May 2020 - Jun 2025
Contributions:32 pushes, 3 branches in 5 years 2 months
uscensusbureau/SABLE
Oct 2017 - Oct 2022
Scraping Assisted by Learning
Contributions:335 commits, 36 PRs, 443 pushes in 5 years 1 month
pythonmachine-learninglearning-byassistedweb-scraping
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