Summary
Neil Shah is a Director of Research and Senior Principal Research Scientist at Snap Inc. with 11 years of experience building and translating user modeling, graph ML, and language-model-driven personalization into production at billion-scale. He leads cross-functional research programs that connect academic rigor with product impact across Growth, Content, Ads, and Safety, while retaining hands-on IC bandwidth to drive high-leverage technical projects. His PhD work at Carnegie Mellon and internships across Microsoft, LLNL, and Twitch underpin deep expertise in anomaly/fraud detection, temporal graph understanding, and recommender systems. Neil publishes and organizes workshops in top ML and IR venues and actively cultivates academic partnerships to accelerate both science and platformization. Based in Seattle, he is as comfortable defining research strategy as he is optimizing scalable GNN training and inference pipelines.
11 years of coding experience
16 years of employment as a software developer
Bachelor of Science, Computer Science, Bachelor of Science, Computer Science at North Carolina State University
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Carnegie Mellon University