Summary
David Weisberger is a Senior Machine Learning Modeler with a decade of experience applying physics-trained rigor and humanities-rooted curiosity to fraud mitigation and product ML at companies including Cash App, Instacart, Hawkfish, pymetrics, and the Hillary campaign. He migrated from German literature to physics and then into data science, blending deep analytical modeling with practical production engineering to limit fraud losses and drive data-informed product decisions. A seasoned practitioner in building and operationalizing ML models, he pairs academic research instincts (including PhD-level physics work) with hands-on experience across political tech, HR analytics, e-commerce, and fintech. Based in New York, he’s known for translating complex signals into robust, scalable systems—and for bringing a rare cross-disciplinary perspective that surfaces unexpected features and causal insights.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.) — unfinished, Physics, (degree unfinished), Doctor of Philosophy (Ph.D.) — unfinished, Physics, (degree unfinished) at Arizona State University
Master of Arts - MA, German Language and Literature, Master of Arts - MA, German Language and Literature at Freie Universität Berlin
Master’s Degree, Physics, Master’s Degree, Physics at San Francisco State University
Data Science Fellow, Data Science Fellow at Galvanize - Denver, Platte
Bachelor's degree, German Literature and Cultural History, Bachelor's degree, German Literature and Cultural History at Columbia University
English, German