William Wu
Principal Data Scientist (Machine Learning)
Singapore
Summary
👤
Senior🎓
Top SchoolWilliam Wu is a Principal Data Scientist based in Singapore with a decade of experience building large-scale recommendation and advertising systems, from CTR/CVR models to fraud detection and promo optimization. He combines deep academic training in computer software and theory with hands-on engineering—shipping production ML pipelines, real-time user representation platforms, and an offline feature store at Grab. William has driven measurable business impact (e.g., double-digit CTR/CVR uplifts, 12% error reduction in supply forecasting) while scaling systems to handle high throughput and low latency. He also contributes to open-source tooling—helping develop the TabNine Jupyter extension—and has led cross-functional teams and mentored engineers, blending model innovation (PNN, multi-task networks) with pragmatic deployment (Kubernetes, TensorFlow, Spark). Quick to learn and focused on industrializing research, he thrives on turning complex algorithms into reliable, production-grade products.
11 years of coding experience
10 years of employment as a software developer
Bachelor's degree, Information Management and Information System, 2009, Bachelor's degree, Information Management and Information System, 2009 at Shandong University of Science and Technology
English, Chinese
Stackoverflow
1,854reputation
531kreached
21answers
5questions
jupyter-notebook
top-5%
tensorflow
top-5%
neural-network
top-5%
python
top-5%
Github Skills (22)
javascript10
docker10
code-completion10
dockers10
go10
jupyter-notebook10
python9
tensorflow9
neural-network9
css7
build-automation7
html7
hidden-markov-model6
keras6
kfp6
Programming languages (15)
Github contributions (5)
codota/jupyter-tabnine
Sep 2019 - Feb 2021
Autocompletion with Deep Learning on Jupyter Notebook
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:84 commits, 9 PRs, 74 pushes in 1 year 5 months
Contributions summary:William primarily contributed to the development of the TabNine extension for Jupyter Notebook. Their work included implementing features for code completion, specifically supporting in-place completion with tab up and down functionality. They also refactored the existing code and fixed bugs. In addition, they added build and deployment scripts with Docker.
deep-learningjupyter-notebook
wenmin-wu/rtb-algorithms
Jul 2016 - Jul 2016
Contributions:5 commits, 3 pushes, 1 branch in 1 day
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