Summary
Qimin Wu is a data and marketing analyst with a decade of experience turning complex datasets into actionable business decisions across real estate, aerospace, and AI product teams. Skilled in SQL, Python, R, Tableau, and analytics platforms, he has built real-time dashboards and machine learning models that improved campaign effectiveness by 27%, boosted engagement, and refined portfolio forecasting. At Baidu he translated technical research on foundation models and retrieval-augmented generation into executive recommendations that influenced product prioritization, and at GE he improved forecasting accuracy through automated model selection. Trained at UCLA Anderson (MS Business Analytics) and UIUC (Econometrics), he blends rigorous econometric thinking with practical data engineering. Based in Beijing with US experience, Qimin pairs product-focused analysis with cross-functional communication to drive measurable outcomes. A self-described "JS noob" who nonetheless leverages Python and visualization tools to deliver high-impact insights, he’s comfortable bridging technical work and strategic storytelling.
9 years of coding experience
Master of Science - MS, Business Analytics, Master of Science - MS, Business Analytics at UCLA Anderson School of Management
Bachelor of Arts - BA, Econometrics and Quantitative Economics, Bachelor of Arts - BA, Econometrics and Quantitative Economics at University of Illinois Urbana-Champaign
Chinese, English