Lead Data Scientist - Financial Crime

About the role

Mastercard is looking for a Lead Data Scientist to join its Financial Crime Solutions team in Toronto. You will design, build, and continuously improve machine‑learning models that detect anomalous transaction behaviour, primarily focused on anti‑money‑laundering (AML) initiatives.

Key responsibilities

• Lead the development and enhancement of AML models that analyse card payment data for illicit activity.
• Own end‑to‑end problem solving, from framing and prototyping to production deployment and monitoring.
• Shape modelling approaches and technical direction in partnership with senior data‑science leadership.
• Analyse large‑scale payments datasets to uncover patterns linked to financial crime.
• Improve model performance, stability, explainability and scalability.
• Collaborate with Engineering and Product teams to ensure reliable production deployment.
• Document model assumptions, limitations, and performance metrics.
• Maintain compliance with regulatory, privacy and security requirements.

Required profile

• Strong Python expertise with experience in standard data‑science libraries.
• Proven track record of designing, deploying and maintaining production‑grade machine‑learning models.
• Experience working with high‑volume transactional or behavioural data.
• Ability to work autonomously, drive outcomes and align with cross‑functional teams.

Required skills

• Python
• PySpark
• Databricks
• MLflow