David Bangor
Predictive Analytics Data Science, Advisor
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolDavid Bangor is a predictive analytics and data science advisor with 11 years of experience translating math-heavy research into operational solutions for energy and wildfire risk management. Based in San Francisco, he currently leads predictive analytics at Southern California Edison, applying numerical optimization, time-series methods, Kalman filtering and causal ML to fuse reanalysis weather data with historical fire records. He previously led a data science team at Kelvin, building reinforcement learning and optimization models for energy applications, and brings a rare blend of applied PDE/numerical analysis and practical ML production experience. A former mathematics instructor and academic researcher, he is comfortable explaining complex quantitative results to non-specialists and designing experiments for real-world impact. Not obviously, his background in functional analysis and ecological modeling informs a principled, model-based approach to anomaly detection and forecasting in high-stakes operational settings.
11 years of coding experience
8 years of employment as a software developer
Master of Arts (M.A.), Mathematics, Master of Arts (M.A.), Mathematics at San Francisco State UniversitySan Diego State University
Github Skills (4)
subversion10
github10
git10
patch10
Programming languages (1)
Github contributions (3)
rognab/Strava-Segment-Classifier
Nov 2014 - Nov 2014
Contributions:19 commits in 7 days
rognab/Road-Route-Planner
Dec 2014 - Dec 2014
Contributions:11 commits in 1 day
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