Yanqing Bao, PhD
About Yanqing Bao, PhD
Yanqing Bao, PhD, is a Senior Data Scientist at Sift with extensive experience in predictive modeling and uncertainty quantification. He has a strong academic background, holding a PhD in Systems Engineering from Vanderbilt University and a Master's degree from Carnegie Mellon University.
Current Role at Sift
Yanqing Bao serves as a Senior Data Scientist at Sift, a position he has held since 2023. In this role, he applies his expertise in data science to enhance the company's capabilities in predictive modeling and decision-making under uncertainty. His responsibilities include conducting experiments, data acquisition, data cleansing, and feature engineering, leveraging his extensive background in the field.
Previous Experience at Sift
Prior to his current role, Yanqing Bao worked at Sift as a Data Scientist from 2021 to 2023. During this two-year tenure, he contributed to various data-driven projects, utilizing his skills in programming and data analysis to support the company's objectives.
Education and Expertise
Yanqing Bao holds a Doctor of Philosophy (PhD) in Systems Engineering from Vanderbilt University, where he also completed a Bachelor of Science (BS) in Civil Engineering at Tongji University. Additionally, he earned a Master of Science (MS) in Advanced Infrastructure Systems from Carnegie Mellon University. His academic background complements his in-depth knowledge of uncertainty quantification and experience in predictive modeling.
Research and Teaching Experience
Yanqing Bao has significant research and teaching experience. He worked as a Research Assistant and Teaching Assistant at Vanderbilt University from 2014 to 2020, accumulating six years in these roles. He also served as a Teaching Assistant at Carnegie Mellon University for 11 months in 2013. His experience includes collaborating with multi-disciplinary teams and developing strong communication and presentation skills.
Technical Skills and Tools
Yanqing Bao possesses strong technical skills in programming languages such as Matlab and Python, along with experience in C, Java, R, and SQL. His expertise extends to data acquisition, data cleansing, and feature engineering, which are essential for effective data analysis and modeling in his current and previous roles.