Jun Seok Lee

Jun Seok Lee is an accomplished data scientist and applied scientist with extensive experience in machine learning and causal inference. At Uber, Jun Seok Lee plays a pivotal role in the Rider Core Product Science Team, leading the ideation, design, and execution of strategic projects, including the development of a causal inference framework and a multi-task ML recommendation model. Prior to this position, Jun Seok Lee contributed as a Data Scientist/Machine Learning Engineer at Bayesian Health and held roles as a Graduate Teaching Assistant and Graduate Researcher at the University of California, Davis. Jun Seok Lee began a career in AI as an Artificial Intelligence Fellow at Insight Data Science and has recently transitioned to a Research Scientist position at Meta. Educational qualifications include a PhD in Theoretical and Mathematical Particle Physics from the University of California, Davis, alongside a Bachelor's degree in Physics and Mathematics from the Korea Advanced Institute of Science and Technology.