Summary
Jason Yang is a software engineer with a strong CS foundation from MIT and a decade of professional experience focused on backend systems and applied machine learning. He has shipped production-grade solutions at startups and enterprises alike, including large-scale NLP deduplication and parallelized address matching at JPMorgan Chase and backend architecture work at Regard and Kensho. His research background in astrophysics-informed ML (processing TESS data with PyTorch) highlights a knack for turning noisy, high-volume data into actionable pipelines. Jason emphasizes clean, maintainable code—reflected in his GitHub focus—and blends rigorous engineering with practical results, such as uncovering millions of duplicate records from massive datasets. Based in the New York City area, he brings both research-level modeling expertise and production engineering discipline to data-intensive systems.
10 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Massachusetts Institute of Technology