Liyu Gong
About Liyu Gong
Liyu Gong is a data scientist with extensive experience in statistical analysis and machine learning. Currently employed at Protective Life, he has previously held positions at several companies, including LabCorp and SAS, and holds a Master's degree in Statistical Science from Duke University.
Current Role at Protective Life
Liyu Gong has been employed at Protective Life as a Data Scientist since 2020. In this role, he applies his expertise in statistical data analysis and machine learning techniques to support various projects. His work involves utilizing programming languages such as R and Python to implement advanced statistical models. Liyu's contributions are integral to the data-driven decision-making processes at Protective Life.
Previous Experience in Data Science and Actuarial Analysis
Before joining Protective Life, Liyu Gong held several positions that contributed to his expertise in data science and actuarial analysis. He worked as an Associate Data Scientist at Protective Life from 2018 to 2020. Prior to that, he completed internships at LabCorp as a Data Scientist Intern in 2017 and at SAS as a Summer Intern in 2016. Additionally, he gained experience as an Actuarial Summer Analyst at United Guaranty Corporation in 2015 and AIA in 2013.
Educational Background in Statistics and Actuarial Science
Liyu Gong holds a Master of Statistical Science from Duke University, where he focused on advanced statistical methodologies. He also earned a Bachelor of Science in Actuarial Science from The Ohio State University. This educational foundation has equipped him with the skills necessary for statistical modeling and data analysis in his professional career.
Expertise in Machine Learning and Statistical Modeling
Liyu Gong possesses significant expertise in implementing machine learning techniques and statistical models. His proficiency in programming languages such as R and Python enables him to conduct advanced statistical data analysis. He has been involved in various projects that require a deep understanding of statistical methodologies, showcasing his hands-on experience in the field.