Liangdong Fan
Lead Data Scientist (Ds Iii) @Chewy
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WORK HISTORY
Lead Data Scientist (Ds Iii) @Chewy
Boston, MA, US
As a Data Scientist at Chewy, I lead end-to-end architecture, productionization, and lifecycle management of machine learning systems for fraud and abuse prevention across our business workflows. My role spans the full model lifecycle, including data analysis, feature development, model training, evaluation, and ongoing performance monitoring in production environments.I partner closely with engineering, product, and risk teams to translate business requirements into scalable modeling solutions. This includes supporting production deployments, validating model behavior across environments, and ensuring model outputs are reliable, interpretable, and aligned with operational needs.Beyond individual model contributions, I help drive continuous improvement through experimentation, performance analysis, and shared best practices. I also contribute to technical discussions and design decisions, with a focus on building maintainable, high-quality data science solutions that deliver long-term business value.
EDUCATION
University of Kentucky
Master's degree, Statistics
University of Kentucky
Doctor of Philosophy (Ph.D.), Nonparametric and Semiparametric regression on medical and finance data sets
Anhui Normal University
Bachelor of Science (B.S.), Statistics
University of Kentucky
Doctor of Philosophy - PhD, Statistics
ABOUT LIANGDONG FAN
I’m a Lead Data Scientist with a Ph.D. in Statistics, focused on building and scaling machine learning systems for fraud prevention and financial crime. I specialize in applying statistical and ML methods to real-world problems where reliability, interpretability, and speed are essential.In my current role, I work on end-to-end model development, from problem framing and feature design to production deployment and monitoring. I collaborate closely with engineering, product, and risk partners to ensure models integrate smoothly into business workflows and deliver measurable impact, while remaining robust and maintainable over time.Previously, I worked in Anti-Money Laundering within the banking industry, developing and validating transaction monitoring models in regulated environments. Across roles, I enjoy translating complex analytical ideas into practical solutions and partnering across teams to drive data-informed decision-making.
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