Yibin Ng
Co-Founder, Chief Data Scientist
Singapore
Summary
👤
Senior🎓
Top SchoolYibin Ng is a data scientist and entrepreneurial technologist with over a decade of experience building and scaling machine learning and signal-processing solutions across industry and research. As Co-Founder and Chief Scientist at EigenAI and former Global Lead of Data Science at SC Ventures (Standard Chartered), he has delivered end-to-end ML systems—ranging from customer 360 and propensity-to-buy models to feature libraries and automated campaign pipelines—that produced measurable cost savings and operational impact. His background spans deep research in signal processing, error-correction and applied cryptography (four patents, including one sold to Marvell) and practical big-data engineering with tools like Spark, Airflow and PySpark. He also teaches advanced data science curricula at NTU and contributes open-source stock-prediction work on GitHub, reflecting both product delivery and research-to-production rigor. Notably, his research in bi-directional noise prediction and secure deduplication has driven meaningful BER and privacy improvements that inform his applied ML work.
10 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Electrical and Computer Engineering, Doctor of Philosophy (Ph.D.) Electrical and Computer Engineering at Carnegie Mellon UniversityBachelor of Engineering (B.Eng.) Electrical and Electronics Engineering, Bachelor of Engineering (B.Eng.) Electrical and Electronics Engineering at National University of Singapore
English, Chinese
Github Skills (9)
forecasting10
pandas10
xgboost10
machine-learning10
forecast10
python10
numpy10
jupyter-notebook9
signal-processing8
Programming languages (2)
Github contributions (5)
NGYB/Stocks
Nov 2018 - Dec 2021
Programs for stock prediction and evaluation
Role in this project:
Data Scientist
Data ScientistContributions:26 commits, 4 PRs, 63 pushes in 3 years 1 month
Contributions summary:Yibin contributed significantly to stock prediction and evaluation programs. Their primary focus involved developing and refining machine learning models for predicting stock returns. This included implementing and debugging scripts using XGBoost, as seen in the iterative development of notebook files, indicating a strong focus on model training, evaluation, and improvement. The user incorporated technical indicators as features, reflecting a deeper understanding of financial analysis and feature engineering.
forecastingsignalstock-marketstock-tradingpython
NGYB/Courses
Nov 2018 - Feb 2025
Contributions:44 pushes, 1 branch, 1 issue in 6 years 4 months
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