Summary
Richard Tseng is a data engineer with 10 years of experience building scalable ETL pipelines, pricing and retention models, and production ML systems across finance and retail. Based in Cambridge, he has driven large performance gains—cutting preprocessing and optimization runtimes by up to 80% at in4mation insights and improving forecasting accuracy that yielded multimillion-dollar P&L benefits during an American Express internship. His background spans Spark, Databricks, Hive, Python, Scala and containerized deployments, and he’s comfortable designing experimental designs, REST APIs, and multi-objective optimization workflows. Richard combines strong quantitative training (MS in Operations Research from Columbia, top-ranked BBA in Statistics) with hands-on engineering: from backtesting macroeconomic strategies to automating large-scale data platforms. He’s particularly adept at turning research-grade methods into production services that shorten model iteration cycles and stabilize long-running ETL. Colleagues would note his knack for squeezing performance from systems and exposing business value through rigorous experimentation.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Business Administration - BBA, Statistics, GPA 3.86/4.0 (4.18/4.3), ranked second among my peers, Bachelor of Business Administration - BBA, Statistics, GPA 3.86/4.0 (4.18/4.3), ranked second among my peers at National Cheng Kung University
Master of Science - MS, Operations Research, Master of Science - MS, Operations Research at Columbia University in the City of New York
Chinese, English