Summary
Jiaming Qu (Jeremy) is a data-driven software engineer-in-training based in New York, pursuing an MS in Data Science at Columbia University after earning summa cum laude in Mathematics from Ohio State. He specializes in designing scalable, data-driven systems with a focus on content recommendation and transportation networks. At NetEase, he enhanced a PB-scale real-time bidding pipeline to 99.9% processing stability, cut fraud losses by 15% through SQL-based log analysis on Spark/Hive, and led data migration to Apache Doris ensuring zero data loss. He also built an ad-traffic analytics system with Prometheus for real-time monitoring and has hands-on software engineering experience from JETZY as a Software Engineer Intern. He previously served as a Student Research Assistant at Columbia University, applying ML and data analysis to research problems. Based in NYC, he is actively seeking summer internship opportunities to apply ML, algorithm design, and system design skills to real-world challenges.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Mathematics, 3.91/4.0 (summa cum laude), Bachelor of Science - BS, Mathematics, 3.91/4.0 (summa cum laude) at 美国俄亥俄州立大学
Master of Science - MS, Data Science, Master of Science - MS, Data Science at Columbia University
English, Chinese