Ling Dai is a Senior Data Scientist with eight years of experience translating complex consumer and retail data into high-impact, revenue-driving analytics for top CPG clients. At Circana (formerly IRI) she led a complete re-architecture of assortment optimization and pricing pipelines—cutting model setup from months to minutes and enabling localized, near real-time decisioning adopted by 20+ major manufacturers. She combines rigorous statistical modeling, experimental design, and production-grade Python/PySpark engineering to deliver solutions that integrate with client applications and APIs. A University of Chicago MA in Computational Social Science and a quantitative double major from Northwestern’s selective ISP inform her blend of academic rigor and product-minded pragmatism. Relocating to Hong Kong in 2025, she’s seeking data science or strategy-facing roles in the region and is particularly interested in applying analytics to culturally driven markets. Outside work she studies mechanical watches and contemporary music culture, exploring how data can reveal the interplay between tradition, taste, and consumer behavior.
8 years of coding experience
5 years of employment as a software developer
Bachelor’s Degree, Double Major in Mathematics & Integrated Science Program (ISP), Bachelor’s Degree, Double Major in Mathematics & Integrated Science Program (ISP) at Northwestern University
Master of Arts - MA, Computational Social Science, Master of Arts - MA, Computational Social Science at The University of Chicago
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