Jing-qiang Goh is a machine learning engineer and former computational physicist with a decade of experience building time series forecasting, anomaly detection, and end-to-end analytics platforms. He has driven product features and nowcasting workflows at DataRobot, built compliance-focused KYC tooling for global payments, and recently focuses on time series platform engineering at Nixtla. Comfortable bridging research and production, he has a track record of reducing model and simulation runtimes by orders of magnitude and translating user needs into robust software. His background in physics and research brings a pragmatic, quantitative rigor to ML system design, while his hands-on work with real-time scheduling and operational constraints highlights an aptitude for applied optimization in complex environments.
10 years of coding experience
14 years of employment as a software developer
Doctor of Science in Technology Physics, Doctor of Science in Technology Physics at Tampere University of Technology 1965-2018
Master of Science (M.Sc.) Physis, Master of Science (M.Sc.) Physis at National University of Singapore
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Jing-qiang Goh - Machine Learning Engineer at Nixtla