Summary
Yuxue Jiang is a data scientist with 10 years of experience combining business acumen and technical rigor to turn operational problems into measurable impact. She has driven high-impact projects at Uber, AxleHire and Kuaishou—building fraud detection rules that saved $50K/month, automating billing workflows to cut marketing effort by 75%, and improving driver operations by 20% through rating models and A/B testing. Proficient in Python, SQL, Hadoop, time-series and regularized models, she translates complex analyses into production-ready pipelines and cross-functional dashboards. Comfortable working with Product, Engineering and Operations, she pairs statistical modeling (LASSO, logistic regression, clustering, PCA) with practical feature engineering and real-time data integration. A Cornell-trained applied economist, she brings a quantitative, product-focused mindset that surfaces non-obvious levers for efficiency and revenue protection.
10 years of coding experience
2 years of employment as a software developer
Master’s Degree, Applied Economics and Management---- Behavioral Finance, 3.77, Master’s Degree, Applied Economics and Management---- Behavioral Finance, 3.77 at Cornell University
Bachelor’s Degree, Business/Managerial Economics, Accounting, Bachelor’s Degree, Business/Managerial Economics, Accounting at University of California, Los Angeles
German