Summary
Shilong Dai is a Technical Associate at TIAA with 11 years of engineering experience, currently focused on AI governance—designing patterns, processes, and review tooling to shepherd AI use cases through their lifecycle. He combines a rigorous academic foundation (MS in Data Science from University of Chicago; BS in Computer Science and Statistics from UNC-CH with near-perfect GPAs) with hands-on MLOps and automation experience, from building Domino training workflows to automating telecom deployments with Ansible, Docker, and Jenkins. Past projects include creating recoverable production runbooks for ETF/benchmark processing, migrating trading workflows to Autosys, and delivering a full-stack financial literacy web app using AWS Amplify and React. Comfortable spanning data wrangling, ML model deployment, and operational resilience, he favors pragmatic solutions that reduce time-to-value—one automation cut a multi-day commissioning task to under three hours. Based in Cary, NC, he brings a blend of academic rigor and production-first engineering to governance problems that require both technical depth and process thinking.
11 years of coding experience
2 years of employment as a software developer
Green Hope High School
Master of Science - MS, Data Science, Master of Science - MS, Data Science at University of Chicago
Bachelor of Science - BS, Computer Science, Statistics, Minor in Math, 3.95 Cumulative GPA, 4.0 Major GPA, Bachelor of Science - BS, Computer Science, Statistics, Minor in Math, 3.95 Cumulative GPA, 4.0 Major GPA at University of North Carolina at Chapel Hill