Provides technical leadership across the overall Analytics function which may have an enterprise mandate.
Provides deep technical knowledge and expertise in client interactions to explain complex data analysis related material.
Developing, maintaining, and enhancing the Enterprise Anti-Money Laundering / Counter-Terrorism Financing (AML/CTF) models/AI solutions to comply with regulatory requirements/changes and internal policies.
Supporting TD's global AML/CTF strategies, addressing emerging risks, and aligning with best industry practice.
Innovating, driving, and supporting initiatives and business as usual operations in multiple functional areas including customer rating, sanctions screening, transaction monitoring, emerging risk, model performance monitoring, analytics and reporting.

Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science)
Graduate's degree preferred with either progressive project work experience or 5+ year of relevant experience; higher degree education and research tenure can be counted
In lieu of 5+ years of relevant experience, we will consider 3+ years of relevant experience
Proficient with Python or equivalent programming language and SQL
Experience in Financial Crimes / Compliance Risk Analytics is a plus
Experience in optimization / testing / tuning of AML/CTF solutions, particularly transaction monitoring systems
Experience in machine learning model development, validation, and deployment; experience with LLM-based solutions a plus
Familiarity with cloud platforms (Azure) and modern data stack tools a plus

Data Scientist III – Financial Crimes Modeling

Key skills