Yihua Astle is a data science professional with substantial hands-on experience in delivering machine learning and advanced analytics solutions in the legal, compliance, finance, and media sectors. She has helped clients solve business problems through optimized algorithms, enhanced models and systems, and efficient workflows. In the last few years, before joining BRG, she helped to build a startup by undertaking research and development, team building, and business development, and improving operational efficiency. She has developed and implemented a stack of machine learning and natural language processing (NLP) technologies for litigation document reviews, compliance monitoring systems, and fact-pattern investigations.
Ms. Astle has led the design and deployment of visualization tools and the infrastructure to support the analytics output for machine-learning projects. Previously, she was a data scientist at Fannie Mae and at a mass media holding company, where she helped build and deploy enterprise-level predictive models that lowered operational costs while improving sales and revenue. She advised senior leaders and executives on pricing, marketing, product design, and client retention and acquisition strategies, leveraging insights from data.
Trained as an economist early in her career, Ms. Astle possesses strong knowledge of econometrics studies, impact evaluations, and statistical analysis. She understands the value of both traditional data analytics and machine-learning solutions.
Ms. Astle did her undergraduate work at the University of Hong Kong, earning a degree in economics and finance. She graduated summa cum laude with a master’s degree in economics and quantitative methods from the University of California, San Diego.
University of California, San Diego
MA, Economics, 2014
University of Hong Kong
BS, Economics and Finance, 2012
Lead data scientist
Senior quantitative associate
Allison Award for Highest Grade Point Average in Graduating Class, 2014
Larry Robinson Research Fellow, University of California, San Diego, 2013
News & Insights
News & Commentary
- ICLGDecember 11, 2019
- BRG press releaseNovember 14, 2019