Senior Manager, AML Model Management

The role:

The AML Analytics Senior Manager, Model Management, will lead the Model Management team within the Anti-Money Laundering (AML) Analytics program. This role is responsible for the full lifecycle of AML models, including development, implementation, optimization, and validation. The manager will also oversee vendor integrations, ensure model governance, and provide comprehensive reporting to oversight bodies. This role will also support AML governance initiatives including risk assessments and internal/external inquiries.

What you’ll do:

• Lead and manage the Model Management team, including performance management, mentorship, and resource allocation.
• Oversee the development, implementation, and maintenance of AML models across multiple product lines (banking, brokerage, lending) to ensure robust risk coverage.
• Manage and optimize AML applications to ensure conceptually sound design, proper implementation, and acceptable performance.
• Act as a key point of contact for Model Risk Management matters, collaborating with internal stakeholders (e.g., Compliance, Technology, Business Units) and external partners (e.g., vendors, regulators).
• Partner with technical teams (developers, program managers, data analysts) to deliver AML technology transformation initiatives related to models and systems.
• Communicate complex model-related information to both technical and non-technical audiences in a clear and concise manner.
• Oversee the research, compilation, and evaluation of large datasets for AML threat detection and model building.
• Direct the building and refinement of experimental models using machine learning and statistical modeling methods (supervised and unsupervised learning).
• Present model performance reports and key metrics to senior management and relevant committees
• Identify and implement process improvements within the Model Management function to enhance efficiency and effectiveness.

What you’ll need:

• Bachelor’s Degree or Master’s Degree in Statistics, Computer Science, Mathematics, Finance, Computer Science, Engineering or other relevant areas.
• 10+ years of experience in the finance industry focusing on BSA/AML, OFAC, or fraud modeling/analytics.
• Strong statistical/data analytical skills, including data quality validation and predictive modeling experience in SQL, R, and/or Python.
• Knowledge of and ability to leverage traditional databases, cloud-based computing, and distributed computing.
• Experience supporting and managing AML governance-related responsibilities, including risk assessments, internal/external audits, and other regulatory requirements.
• Demonstrated ability to communicate effectively with all levels of the organization and across different business lines.
• In-depth knowledge of AML regulations and the USA PATRIOT Act.
• Familiarity with regulatory guidance on Model Risk Management (Federal Reserve SR Letter 11-7, OCC Bulletin 2011-12, FDIC FIL 22-2017, DFS504).
• Experience with data visualization (e.g., Tableau) and data monitoring systems (e.g., DataDog, Monte Carlo).
• Experience with cloud data infrastructure (e.g., Snowflake), automated transaction monitoring (e.g., Verafin), and customer/transaction screening (e.g., LexisNexis).
• Experience with infrastructure automation software (e.g., Terraform) and familiarity with virtualization and containerization (e.g., Docker, Kubernetes).
• CAMS certification preferred.