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.
Develops, maintains, and enhances the Enterprise Anti-Money Laundering / Counter-Terrorism Financing (AML/CTF) models/AI solutions to comply with regulatory requirements/changes and internal policies.
Supports TD's global AML/CTF strategies, addresses emerging risks, and be in accordance with best industry practice.
Works closely with business owners to identify opportunities and serves as an ambassador for data science.
Uses a wide range of programing languages (e.g. Python) and techniques for extracting and preparing data, applying statistics and various advanced analytics, along with business acumen to extract insights from the big data.

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+ years of relevant experience; higher degree education and research tenure can be counted
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