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
Responsible for developing, maintaining, and enhancing the Enterprise Anti-Money Laundering / Counter-Terrorism Financing (AML/CTF) models/AI solutions
Addresses emerging risks and adheres to best industry practices
Works independently on activities related to analysis, design and support of technical data management solutions on various projects

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
Strong foundation in regression, classification, and machine learning models and anomaly detection techniques
Proficiency with Python and SQL is a must
Experience in Financial Crimes / Compliance Risk Analytics is a plus
Hands-on experience with GenAI applications is a strong plus, including but not limited to fine-tuning or prompting LLMs, ability to build analytical solutions using LLM APIs, and use GenAI applications to develop data labeling solutions

Data Scientist III – Financial Crime Risk Modeling

Key skills