Senior Analyst / Data Scientist (Compliance Strategy, Data Intelligence & Innovation)
Company: Mastercard
Location: Toronto, Canada, Canada
Type: Full-time
Posted: 2026-05-21
About this role
- The Compliance Strategy, Data Intelligence & Innovation Group (CSDII) helps detect, investigate, and prevent financial crime across the transaction lifecycle
- We work closely with internal Compliance, Legal, Technology, and Operations teams to strengthen anti-money laundering (AML), counter-terrorist financing (CTF), and sanctions compliance by using data to obtain actionable insights aiming to continuously improve our network
- In the Sr Analyst, Data Scientist role, you will support transaction and sanctions monitoring programs by performing ongoing tuning of alerts and measuring what works
- Support tuning and optimization of sanctions screening and transaction monitoring scenarios, with a focus on alert quality, false positive reduction, and regulatory defensibility
- Design, test, and validate scenario risk indicators and analytical features using transactional, entity, and behavioral data
- Document insights across the scenario lifecycle, including hypothesis development, tuning analysis, validation, and production readiness
- Monitor and assess scenario and model performance to ensure explainability, auditability, and regulator readiness
- Prepare clear summaries of scenario performance, trade offs, and residual risk for compliance leadership and partners
- Build and maintain reusable Python and SQL code to pull, clean, and analyze monitoring data while assuring outputs are accurate, repeatable, and easy to audit
- Look for ways to automate repeatable manual work (e.g., data preparation, recurring reports, and quality checks) and help test simple solutions with technology partners
- Support AI and advanced analytics work (e.g., help create features, check how models perform over time, and summarize results in a way that is easy to understand)
- Turn data analysis into clear notes, visuals, and simple documentation that explains what was done, why, and what changed
- Help improve data quality by reconciling key fields, flagging unusual patterns, and support...