Kai Yin
About Kai Yin
Kai Yin is a Staff Data Scientist/Machine Learning Scientist at Expedia Group, specializing in pricing optimization and demand modeling. He has extensive experience in data science roles across various companies and holds a Ph.D. in Transportation Engineering from Texas A&M University.
Title
Kai Yin is a Staff Data Scientist and Machine Learning Scientist currently working at Expedia Group in Austin, Texas.
Company
Kai Yin has been a valuable member of Expedia Group since 2021, where he applies his expertise in data science and machine learning to various projects, focusing on pricing optimization and demand modeling. Expedia Group is known for its comprehensive travel services and innovative technology solutions.
Professional Background
Kai Yin has a diverse professional background that spans across multiple companies and roles. He served as a Staff Data Scientist at HomeAway.com Inc from 2019 to 2020, and as a Senior Data Scientist from 2017 to 2018 at the same company. Prior to this, he worked as a Senior Modeling Analyst/Data Scientist at Nomis Solutions from 2014 to 2017. Kai's early career includes research-focused roles such as Research Faculty at the University of Nevada, Reno, and a Postdoctoral Researcher at the Zachry Department of Civil and Environmental Engineering at Texas A&M University.
Education and Expertise
Kai Yin holds a Ph.D. in Transportation Engineering from Texas A&M University, where he also worked as a Graduate Research Assistant. He earned his M.S. in Signal and Information Processing from Beijing Normal University and a B.S. in Information and Computing Science from Beijing Jiaotong University. Kai is specialized in pricing optimization, demand modeling, causal inference, A/B testing, and experimental design.
Early Career and Internships
Kai Yin's early career includes several internships and research roles that laid the foundation for his expertise in data science and engineering. He worked as an intern at SAS in Beijing, China, and as a Guest Student Research Assistant at the Chinese Academy of Meteorological Sciences. These experiences provided him with valuable insights and skills that he has effectively applied throughout his career.