Summary
Chuanze Cai is a Data Scientist in New York with nine years of experience turning complex data into business impact, from automated ETL pipelines to productionized machine learning at scale. He has led cross-functional campaigns at Aetna that combined clinical literature, claims data, and Gradient Boosting models to identify cost-saving opportunities and drive targeted patient outreach with measured A/B tests. Comfortable bridging technical and non-technical audiences, he has built interactive React visualizations and REST APIs for the UN and created dashboards that changed marketing and product decisions across companies. With an MS in Business Analytics and a math background, he blends rigorous quantitative methods with practical engineering—often integrating disparate data sources into automated Hive and Airflow workflows. A less obvious strength is his track record of translating ambiguous requirements into measurable roadmaps that improve advertiser retention and campaign ROI.
9 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Mathematics and Computing Science, 3.5/4.0, Bachelor's degree, Mathematics and Computing Science, 3.5/4.0 at Hefei University of Technology
Master of Science (M.S.), Business Analytics, 3.6/4.0, Master of Science (M.S.), Business Analytics, 3.6/4.0 at Fordham Gabelli School of Business
Chinese, English