Kai Li
About Kai Li
Kai Li is a Lead Data Scientist at CCC Intelligent Solutions, where he has worked since 2013. He holds a PhD in Mathematics and Statistics from the University of Massachusetts Amherst and has developed deep learning models for auto insurance claims processing.
Work at CCC Intelligent Solutions
Kai Li has served as the Lead Data Scientist at CCC Intelligent Solutions since 2013. In this role, he has led various initiatives focused on enhancing data-driven decision-making processes. His work includes the development of an eligibility score utilizing deep learning models, which allows for the processing of auto insurance claims without human intervention. This innovation aims to streamline operations and improve efficiency within the organization.
Education and Expertise
Kai Li earned a Bachelor of Science degree in Mathematics from the University of Science and Technology of China, where he studied from 2003 to 2007. He furthered his education at the University of Massachusetts Amherst, obtaining a PhD in Mathematics and Statistics between 2007 and 2013. His academic background provides a strong foundation for his expertise in data science and analytics.
Background
Before joining CCC Intelligent Solutions, Kai Li worked at the University of Massachusetts Amherst as a Teaching Assistant from 2007 to 2013. During this time, he supported various academic programs and contributed to the educational development of students. He also completed a summer internship at Discover Financial Services in 2013, where he focused on resolving data discrepancies during a data lake migration.
Achievements
Throughout his career, Kai Li has led significant projects that have impacted the insurance and data analytics sectors. He guided a team in analyzing the effects of Advanced Driver-Assistance Systems (ADAS) on repair costs and part sales, which revealed issues with mislabeled input data. Additionally, he redesigned the Predictive Method of Inspection engine, resulting in a 39% improvement in classification accuracy, which has the potential to save millions for customers.