Summary
Tianqi Liu is a data-focused master's student in Statistics & Data Science at Carnegie Mellon with eight years of analytical experience spanning startups and healthcare. He founded Qi DataCraft Innovations, building automated Python and PySpark pipelines, PostgreSQL schemas, and weekly reporting that processed hundreds of thousands of HHS/CMS records to monitor hospital capacity and COVID trends. Prior roles include a marketing analytics project using R and RShiny to drive ad strategy and an Optum capstone where he reduced prediction error by 20% using ensemble and neural models on billions of observations in an Azure ETL pipeline. Tianqi combines strong quantitative foundations (3.96 GPA) with practical engineering—deploying fast, reproducible data workflows and visual reporting—and has taught probability theory as a TA. He often bridges economics-style thinking with scalable data engineering, making him adept at turning complex health and marketing datasets into actionable insights.
8 years of coding experience
Master's degree, Statistics & Data science, 3.96, Master's degree, Statistics & Data science, 3.96 at Carnegie Mellon University
Bachelor's degree, Economics & Statistics, 96.1/100, Bachelor's degree, Economics & Statistics, 96.1/100 at Sungkyunkwan University