Zhishi Wang
Applied Scientist at Amazon
Greater Seattle Area United States
Summary
🤩
Rockstar🎓
Top SchoolZhishi Wang is an applied scientist with 11 years of experience blending statistical rigor and production ML to solve business problems across supply chain, marketing science, and finance. With a PhD in Statistics from University of Wisconsin–Madison and early math training from Zhejiang University, he brings deep quantitative foundations to causal inference and optimization work at Amazon and prior roles at Uber, Wells Fargo, and KPMG. He contributes to open-source Bayesian tooling—improving backend MAP estimation and Stan integrations in the well-regarded orbit forecasting library—demonstrating hands-on expertise in probabilistic modeling and numerical methods. Known for turning complex inference concepts into robust, production-ready systems, he balances research-grade thinking with pragmatic engineering to drive measurable impact.
10 years of coding experience
7 years of employment as a software developer
PhD, Statistics, PhD, Statistics at University of Wisconsin-MadisonBS & MS, Mathematics, BS & MS, Mathematics at Zhejiang University
English, Chinese
Github Skills (5)
bayesian-statistics10
bayesian10
stan10
python10
documentation8
Programming languages (2)
Github contributions (5)
uber/orbit
Jan 2020 - Jul 2022
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:12 releases, 115 reviews, 315 commits in 2 years 5 months
Contributions summary:Zhishi primarily focused on enhancing the backend logic of the Orbit package. The contributions involved improvements to MAP estimation, including a fallback to the Newton optimizer and fixes to concatenation issues. Further commits show improvements to docstrings. The user's work demonstrates a solid understanding of Bayesian forecasting methods and the Stan programming language used by the project.
forecastingpythonregression-modelstimeseries-forecastingforecast
wangzhishi/test
Oct 2015 - Oct 2020
Contributions:14 pushes, 4 branches in 5 years 1 month
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