Hang Zhang
Principal Data & Applied Scientist Manager
Redmond, Washington, United States
Summary
👤
Senior🎓
Top SchoolHuanan Zhang is a senior machine learning engineering leader with 11 years of experience building large-scale relevance and personalization systems, currently leading search relevance efforts at Atlassian after a multi-year tenure at Microsoft. At Microsoft he architected production pipelines that linked billions of URLs to hundreds of millions of business IDs, launched Topic Search for Bing/Bing Maps, and advanced personalization using LLMs and RAG across cross-platform signals. He combines hands-on data science—contributing to Azure ML sample and TDSP utilities—with team leadership, shipping categorization-as-a-service and end-to-end local search stacks at scale. With a PhD in computer science and a track record of turning research-grade models into robust production services, he’s adept at bridging product, UX, and engineering to improve real-world search outcomes.
11 years of coding experience
13 years of employment as a software developer
Master Automation, Master Automation at Tsinghua UniversityMaster of Science Statistics, Master of Science Statistics at Rutgers University
Chinese
Github Skills (15)
data-visualizations10
pandas10
jupyter-notebook10
data-visualization10
data-visualisation10
machine-learning10
python10
data-science10
data-analysis10
modeling9
r9
trainings9
feature-engineering9
scikit7
scikit-learn7
Programming languages (5)
Github contributions (5)
Azure/Azure-TDSP-Utilities
Sep 2016 - Aug 2017
Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science
Role in this project:
Data Scientist
Data ScientistContributions:36 commits, 5 PRs, 37 pushes in 11 months
Contributions summary:Hang contributed to the development of interactive data exploration and reporting tools. Their work involved modifying and improving existing Jupyter notebooks (IDEAR) using Python, specifically focusing on functionalities such as data summarization, descriptive statistics, variable interaction analysis, and data visualization through t-SNE. They also fixed bugs and updated R script references within the project.
data-science
Azure-Samples/Azure-MachineLearning-DataScience
Jan 2015 - Aug 2017
Role in this project:Data Scientist
Data ScientistContributions:169 commits, 13 PRs, 154 pushes in 2 years 6 months
Contributions summary:Hang primarily contributed to the data science process within the repository. Their work focused on creating, modifying, and integrating iPython Notebooks that involved data processing, feature engineering, and model training. The user’s changes involved tasks like renaming notebooks, modifying raw text within notebooks, and merging branches, suggesting a focus on the data science workflow and model exploration.
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