Summary
Yumeng Wang is a data science analyst with 11 years of experience who recently earned an MS in Management Science & Engineering (Data Science track) from Stanford and holds dual degrees in Statistics & Analytics and Economics from UNC Chapel Hill. She combines end-to-end technical fluency—from Python, R, and C++ to PySpark, Kafka, dbt, and cloud platforms like GCP and Snowflake—with applied ML skills in TensorFlow, PyTorch, and RAG to move models from prototype to production. Her background includes analytics and ETL work at Amazon and internships at TikTok and Intel, plus socio-economic research at Duke, giving her both industry and academic rigor. Now based in the San Francisco Bay Area and currently at Carvana, she focuses on real-time data pipelines, model deployment, and creating actionable dashboards. Colleagues appreciate that she pairs a perfect academic record (Stanford 4.0 GPA) with a practical bias for shipping reliable, production-ready analytics.
11 years of coding experience
1 year of employment as a software developer
Bachelor of Science, Bachelor of Arts, Statistics and Analytics; Economics, 3.91/4.0, Bachelor of Science, Bachelor of Arts, Statistics and Analytics; Economics, 3.91/4.0 at University of North Carolina at Chapel Hill
Minor, Information Science, Minor, Information Science at UNC School of Information and Library Science
Master's degree, Management Science and Engineering (Data Science Track), 4.0/4.0, Master's degree, Management Science and Engineering (Data Science Track), 4.0/4.0 at Stanford University
English, Chinese, Japanese