Yuji Tamiya

Data Scientist

Chiyoda, Japan
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts

Summary

👤
Senior
🎓
Top School
Yuji Tamiya is a data scientist with eight years of experience applying statistical modeling and machine learning across FinTech, ad-tech, and IoT domains. With a PhD in Mathematical Science and a physics background, he blends rigorous quantitative methods with practical product-focused analytics—examples include ad-effect evaluation, lead scoring, and event detection in sensor time series. At Money Forward he leads data utilization for card products and previously built dashboards, causal analyses, and ML proof-of-concepts at Repro and GRI. He contributes to open-source documentation for statsmodels, improving clarity in time-series state-space modules, which reflects his attention to reproducibility and communication. Based in Chiyoda, Tokyo, he is skilled in Python, SQL, and GCP (BigQuery, Looker Studio) and often bridges research-grade methods with production-ready tooling.
code8 years of coding experience
job3 years of employment as a software developer
book学士号,修士号, Physics, 学士号,修士号, Physics at 早稲田大学 WASEDA University
bookDoctor of Science, Mathematical Science, Doctor of Science, Mathematical Science at Hokkaido University
languagesJapanese, Chinese
github-logo-circle

Github Skills (6)

statistics10
python10
documentation10
latex9
data-science8
econometrics8

Programming languages (5)

RustJavaScriptVueGoPython

Github contributions (5)

github-logo-circle
statsmodels/statsmodels

Jan 2021 - Mar 2021

Statsmodels: statistical modeling and econometrics in Python
Role in this project:
userTechnical Writer
Contributions:4 reviews, 22 commits, 5 PRs in 1 month
Contributions summary:Yuji primarily focused on improving documentation within the `statsmodels/statsmodels` repository. Their contributions involved correcting LaTeX errors and typos in the documentation, adding parameter descriptions, and linking relevant documentation sections. These changes enhance the clarity and accuracy of the project's documentation. The edits were concentrated on the `statsmodels/tsa/statespace/structural.py` file.
forecastingpythonregression-modelsstatsmodelsstatistics
Contributions:142 commits, 95 pushes, 1 branch in 1 month
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial