Summary
Yao Yao is a data scientist with nine years of multidisciplinary experience combining production ML, analytics, and automation across ecommerce, media, and research settings. Based in Chicago, he has built end-to-end solutions—from Python trading bots that generated substantial profit to hybrid recommendation engines, large-scale time-series forecasting on Azure, and computer-vision A/B tests to boost conversions. He blends hands-on engineering (Selenium, Databricks/Spark, Celigo, Shopify Liquid) with statistical rigor (ARIMA, XGBoost, LDA/PCA, HMM) and has led presentations and SOPs that turned data insights into operational change, including ISO-driven waste reductions. Notably, he migrates recurring high-value customers across platforms and automated complex logistics workflows, cutting manual bottlenecks. His background in materials engineering and lab research informs a meticulous, experimental approach to modeling and feature engineering.
9 years of coding experience
6 years of employment as a software developer
B.S.E Material Science Engineering, B.S.E Material Science Engineering at University of Michigan
International Baccalaureate Diploma, International Baccalaureate Diploma at Upper Arlington High School
Master of Business Administration - MBA non degree courses, Master of Business Administration - MBA non degree courses at Oakland University
Master of Science - MS Data Science, Master of Science - MS Data Science at Southern Methodist University
German, English, Chinese, Japanese