Financial Crimes Compliance Modeling & Analytics Manager

About the role

The BSA/AML & Sanctions compliance team oversees Mercury's AML & Sanctions program. The Financial Crimes Compliance Modeling & Analytics Manager will enhance FCC detection and screening models, develop and maintain transaction monitoring and sanctions screening models, and build analytics to track FCC program health.

Responsibilities

• Conduct in-depth analysis of customer, transaction, alert, TM rules, risk ratings, and more using SQL and analytical tools
• Use data-driven methods to improve, design, implement, and maintain FCC models, including transaction monitoring, sanctions screening, and relevant models
• Develop bespoke transaction monitoring rules and sanctions screening logic tailored to Mercury's specific AML and sanctions risk
• Partner with Compliance, Product, and Data leaders to translate regulatory requirements into effective analytical frameworks
• Tell stories with data to enable stakeholders to understand analytics output clearly and compellingly
• Interpret analytics outputs to identify genuine risk signals and communicate their significance to compliance and business stakeholders
• Create and maintain detailed documentation on FCC model configurations, including scenarios, thresholds, segments, tuning, false positive rules, and changes over time
• Evaluate and tune existing detection models and rules to minimize false positives while maintaining regulatory rigor
• Identify new typologies, emerging risks, and evolving financial crime trends using data-driven methods
• Support Model Risk Management to validate and monitor model performance against internal and regulatory standards

Requirements

• Bachelor's degree in a quantitative field (e.g. Computer Science, Engineering, Statistics, Mathematics, or related) with 8+ years of experience conducting in-depth data analytics, ideally with 5+ years in FCC or AML/Sanctions related analytics roles
• Deep understanding of AML and Sanctions fundamentals, including principles and regulations
• Outstanding skills with standard analytical tools; top-notch SQL skills required, experience with Python or similar preferred, and familiarity with modern ML tooling (e.g. scikit-learn, XGBoost) a plus
• Experience developing, tuning, and maintaining machine learning or rule-based detection models, with an understanding of how to rigorously challenge model performance and limitations
• Experience identifying ways to improve both data-related and operational efficiencies
• A healthy dose of skepticism combined with a constructive, solution-oriented approach
• Comfort operating with ambiguity and synthesizing fragmented technical, operational, and business context into a clear understanding of how models work
• High agency and adaptability, able to find the highest-leverage work in a fast-moving environment with evolving priorities
• Curiosity about how AI/ML is applied to financial crime detection, and openness to modern tooling as the function evolves
• Exceptional attention to detail across documentation, testing artifacts, and quantitative analysis
• Strong written and verbal communication skills; able to explain model risk and analytics findings to both technical and non-technical stakeholders

Qualifications

• None specified

Skills

• SQL
• Python or similar programming language
• Modern ML tooling (e.g. scikit-learn, XGBoost)

Benefits

• Base salary
• Equity (stock options/RSUs)
• Benefits

Pay

• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $166,600 - $208,300
• US employees outside of the New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $149,900 - $187,500
• Canadian employees (any location): CAD $157,400 - $196,800

Schedule

• N/A