Yuman (Becky) Liang
About Yuman (Becky) Liang
Yuman (Becky) Liang is a Data Scientist at Harley-Davidson Motor Company in Los Angeles, California, where she has worked since 2018. She has a strong background in data analysis and predictive modeling, with previous roles at various companies including LotLinx, Inc. and Citi.
Work at Harley-Davidson
Yuman (Becky) Liang has been employed at Harley-Davidson Motor Company since 2018 as a Data Scientist. In this role, she has contributed to various data-driven projects in Los Angeles, California. Prior to her current position, she served as a Senior Analyst in Consumer Insights and Analytics at Harley-Davidson from 2017 to 2018 in Milwaukee, Wisconsin. During her tenure, she focused on enhancing the company's understanding of consumer behavior and improving data analytics processes.
Education and Expertise
Yuman Liang holds a Master of Science (MS) degree in Data Science from DePaul University, which she completed from 2014 to 2016. She also earned a Bachelor of Business Administration (B.B.A.) in International Business from Guangdong University of Finance and Economics, graduating in 2014. Her expertise includes crafting analytical roadmaps and defining business problems, which she develops in collaboration with cross-functional teams.
Professional Background
Yuman Liang's professional background includes various internships and roles prior to her current position. She worked as a Digital Strategy Intern at LotLinx, Inc. for three months in 2016 and as a Data Analyst Intern at Jane Addams Resource Corporation for two months in the same year. Additionally, she has experience as an Interpreter at the Canton Fair in 2013 and participated in the Young Talent Program at Citi in Guangzhou, China, also in 2013. Earlier in her career, she completed a Management Enhancement Program Internship at AIA in Hong Kong in 2012.
Achievements in Data Science
In her role as a Data Scientist, Yuman Liang has achieved significant results, including reducing the complexity of the product portfolio by 40% through redundancy detection. She developed a predictive model pipeline on a cloud-based system utilizing Azure with a Spark cluster. Additionally, she increased the customer conversion rate by 44% by identifying key customer interactions that enhance the likelihood of motorcycle purchases.