Linda Ye
About Linda Ye
Linda Ye is the AVP II of Data Science | Healthcare AI at Bristol Myers Squibb, with extensive experience in healthcare AI and data science.
Current Role at Bristol Myers Squibb
Linda Ye is presently serving as AVP II, Data Science | Healthcare AI at Bristol Myers Squibb in California, United States. She is responsible for building healthcare platforms powered by large-scale embedded AI cores to streamline various healthcare processes. Her work focuses on healthcare utilization management, network steerage, clinical coding, provider network management, population health management, clinical decision support, telehealth, and in-home care.
Previous Experience at Anthem, Inc.
From 2018 to 2022, Linda Ye worked as Lead Data Science at Anthem, Inc. in California, United States. During her four-year tenure, she led data science initiatives and was pivotal in conceptualizing, developing, and deploying numerous AI/ML models to address complex healthcare challenges.
Roles at Knowledgent and Weill Medical College of Cornell University
Linda Ye held the position of Senior Data Scientist at Knowledgent in Warren County, New Jersey from 2015 to 2018. Prior to that, she worked as a Neuroscientist in Systems and Computational Neuroscience at the Brain and Mind Research Institute of Joan & Sanford I. Weill Medical College of Cornell University from 2012 to 2015.
Academic Background and Research
Linda Ye completed her Doctor of Philosophy (PhD) in Neuroscience and Molecular Biology at The Johns Hopkins University from 2001 to 2006. She also holds a Master of Science (MS) in Neuroscience and Physiology from Peking University Health Science Center. Additionally, Linda completed her medical science studies at the University of Traditional Chinese Medicine.
Expertise in AI/ML Models in Healthcare
Linda Ye has conceptualized, developed, and deployed close to 1,000 AI/ML models in the healthcare industry. Her expertise lies in translating complex healthcare questions into data science problems and delivering significant financial results, business value, and strategic growth through these models.