Eugene Yan works at the intersection of machine learning and product, building pragmatic ML systems that serve customers. He is currently an Applied Scientist at Amazon, where his focus is taking models out of notebooks and into applications that create real value at scale.

Before Amazon, Eugene led the data science teams at Lazada and uCare.ai, experiences that taught him how machine learning succeeds or fails in production: framing problems around products, collaborating across engineering and business, and shipping systems that hold up under real traffic. He often shares these lessons through talks and podcast conversations on applied ML, ML systems, and data science careers.

Eugene is also a prolific writer whose essays at eugeneyan.com cover applied machine learning, ML in production, technical writing, and career growth for data professionals. His practical, experience-based approach has made his writing a staple for practitioners, and he shares shorter updates as @eugeneyan on Twitter.