Quantitative Model Analyst 3 - AML

About the position This role is an individual contributor position within the Bank’s Enterprise Financial Crime Compliance (EFCC) organization. The person in this role will join a team of Financial Intelligence Unit (FIU) analysts which focuses on the ongoing monitoring, testing, and governance of AML Transaction Monitoring models. The individual will partner closely with model owners, Model Risk Management, internal and external auditors, and senior leadership to evaluate model behavior, identify emerging risks, and support enhancements to AML monitoring capabilities across the enterprise. This team is integral to maintaining and enhancing the Bank’s Anti-Money Laundering Transaction Monitoring systems. The ideal candidate for this role should possess a strong eye for code review, thorough understanding of model risk, previous experience with BSA/AML monitoring tools, and be familiar with SAS, SQL, and Python. Moreover, candidates should demonstrate robust skills in data science, model evaluation, and documentation of findings. This individual is expected to be highly self-driven, well-organized, and efficient in time management, capable of handling multiple tasks at once.

Responsibilities

• Execute and document periodic testing, validation support, and performance reviews in alignment with regulatory expectations and internal risk standards.
• Review and challenge model behavior, limitations, and assumptions; identify potential control gaps and recommend remediation actions.
• Conduct comprehensive code reviews and code change assessments for AML Transaction Monitoring models to ensure alignment with documented intent, coding standards, and regulatory requirements.
• Provide clear, constructive feedback to model and code owners, supporting effective issue resolution and continuous improvement.
• Maintain and enhance internal tracking tools supporting code review and governance activities.
• Assess model threshold & sampling soundness through Below‑the‑Line (BTL) reviews and support ongoing calibration decisions
• Prepare and present materials for audiences including senior leadership, Model Risk Management, Corporate Audit, and regulatory partners.

Requirements

• Bachelor’s degree in a quantitative field, and five or more years of relevant experience OR MA/MS in a quantitative field, and three or more years of related experience OR PhD in a quantitative field, and less than two years of related experience
• Strong eye for code review
• Thorough understanding of model risk
• Previous experience with BSA/AML monitoring tools
• Familiarity with SAS, SQL, and Python
• Robust skills in data science, model evaluation, and documentation of findings
• Highly self-driven, well-organized, and efficient in time management, capable of handling multiple tasks at once.

Nice-to-haves

• Experience working with quantitative models, analytics, or monitoring frameworks in a regulated environment
• Proficiency in SAS, SQL, and Python for data analysis, testing, and automation
• Strong analytical skills with attention to detail and the ability to evaluate complex model behavior
• Experience supporting AML/BSA Transaction Monitoring systems or financial crime detection tools.
• Understanding of AML best practices and regulatory expectations.
• Ability to work independently while managing multiple priorities in a fast-paced environment
• Ability to clearly communicate (verbally and in writing) model performance, risks, and recommendations, tailoring technical depth to the target audience
• Self‑directed problem solver who identifies gaps and resolves issues independently

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law