Charles Tsang
Charles is a Staff Data Scientist at Glass Lewis, where he builds AI tools that turn messy documents into structured data. Before that, he did product analytics at Instagram and Zynga, and consulting at EY and KPMG. He also teaches data science in the Master of Mathematical Finance program at the University of Toronto.
Besides work, Charles is a big fan of Pokemon and Digimon. In his free time, he also enjoys playing basketball and soccer.
Charles has a Golden Doodle named Pudding, he is very energetic and rarely listens to commands.
Experience
- AI Engineering: Production AI apps that extract data from unstructured documents.
- Clustering: K-means segmentation of funds by voting behaviour, aligned with Glass Lewis's views.
- Machine Learning: SageMaker classifiers to flag high-priority claim findings.
- Operational Analytics: Throughput and quality metrics to optimize workforce efficiency.
Data science lead for the 0→1 launch of Intent Aware Ads on Instagram.
- Analyses that drove product decisions
- A/B test design and readouts
- Success metrics and stakeholder reporting
Growth pod, Words with Friends: data science initiatives that shaped the product roadmap.
Tech lead manager for data science and data engineering teams.
- Data science maturity assessment
- Spark pipelines on Hadoop for an insurer
- Reinforcement learning for collections at a Tier I bank
Data science and financial risk management consulting.
Validated commodity and equity derivatives pricing models for mark-to-market and CCR.
Teaching full teaching history →
MMF1922H Data Science, every Sep–Oct in the MMF program.
MAT133Y Calculus and Linear Algebra for Commerce.
latest posts
| Oct 31, 2026 | "I Don't Know, AI Wrote It" |
|---|---|
| Sep 12, 2026 | Causal Impact for Product Data Science |
| May 27, 2026 | The K-Means Paradox |
