Quantitative Model Analyst - 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) quantitative analysts responsible for the ongoing monitoring, testing, analytical review, 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 will have experience evaluating quantitative models or monitoring frameworks in a regulated environment and a demonstrated ability to analyze complex data, investigate changes in model behavior, and develop well-supported conclusions. Candidates should possess a strong understanding of model risk concepts, performance monitoring, sampling methodologies, and root cause analysis. Proficiency in SAS, SQL, and Python for data analysis, testing, automation, and code review is highly desirable. The successful candidate will be able to assess whether code logic, data inputs, transformations, and outputs align with documented intent. Strong written and verbal communication skills are essential, as findings and recommendations must be effectively communicated to model owners, Model Risk Management, auditors, regulators, and senior leadership. This individual is expected to be highly self-driven, well-organized, and efficient in time management, capable of handling multiple tasks at once. Team responsibilities include performing ongoing monitoring and performance assessments of AML Transaction Monitoring models, conducting comprehensive code reviews and code change assessments, executing below-the-line testing of model thresholds, and performing detailed analytical research to understand model behavior changes, emerging trends, and the underlying drivers of observed performance shifts. Each task requires comprehensive, well‑structured documentation of analyses and conclusions such that work can be independently understood, reviewed, and defended without additional explanation.

Responsibilities

• Conduct in-depth analytical research into model performance and behavior changes, including investigation of shifts in alert volumes, customer populations, and transaction patterns to identify underlying drivers and assess potential model impacts.
• Execute and document periodic testing, 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.
• 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 required with at least 8 years of relevant experience OR MA/MS in a quantitative field, and five or more years of related experience OR PhD in a quantitative field, and four or more years of related experience.
• Strong written and verbal communication skills are essential.
• Highly self-driven, well-organized, and efficient in time management, capable of handling multiple tasks at once.
• Comprehensive, well‑structured documentation of analyses and conclusions such that work can be independently understood, reviewed, and defended without additional explanation.

Nice-to-haves

• Demonstrated ability to analyze complex datasets, conduct statistical assessments and exploratory research, and translate findings into actionable insights regarding model behavior, performance trends, and emerging financial crime risks.
• Strong understanding of quantitative modeling concepts, including model drivers, segmentation strategies, threshold optimization, performance monitoring, and root cause analysis.
• 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