Financial Crimes Compliance Modeling & Analytics Manager

About the role

This role focuses on strengthening Mercury's financial crime compliance framework by improving detection models. The work involves deep analysis of customer data, transactions, and alerts using SQL and other tools. A key responsibility is to develop, implement, and maintain models for transaction monitoring and sanctions screening, tailoring them to Mercury's specific risks. This ensures the company protects its customers and the financial ecosystem from illicit activities while simplifying banking for entrepreneurs.

The manager will collaborate with Compliance, Product, and Data leaders to convert regulatory requirements into actionable analytical strategies. This includes developing bespoke rules and logic to address anti-money laundering (AML) and sanctions risks. A crucial aspect of the role is to interpret analytical outputs to identify genuine risks and communicate these findings clearly to both compliance and business stakeholders, ensuring that data insights drive effective risk mitigation.

Success in this position means continuously evaluating and tuning existing detection models to reduce false positives while maintaining regulatory standards. The role also involves identifying new financial crime typologies and emerging risks through data-driven methods. The manager will partner with Model Risk Management to validate models and monitor their performance, ensuring compliance with internal policies and external regulations.

The base salary for this role ranges from $149,900 to $208,300 USD, with specific amounts varying by geographic location within the US and Canada.

Skills that matter here

• SQL: This role requires expert SQL skills for in-depth analysis of customer data, transactions, and alerts.
• Python: Experience with Python is preferred for developing and maintaining FCC models and analytical tasks.
• machine learning: Familiarity with modern machine learning tooling is a plus, and experience developing and tuning ML detection models is required.
• data analytics: The role involves conducting in-depth data analytics to improve financial crimes compliance detection and identify new typologies.

Who this role suits

• Someone with a strong background in quantitative fields and at least five years in FCC or AML/Sanctions analytics.
• An individual who can operate effectively with ambiguity, synthesizing complex information into clear understandings of how models function.
• A person with a healthy degree of skepticism, a solution-oriented approach, and high adaptability to evolving priorities.
• A candidate who is curious about AI/ML applications in financial crime detection and open to modern tooling.

From the employer

Responsibilities

• Use SQL and other analytical tools to conduct in-depth analysis of Mercury's customers, transactions, alerts, TM rules, risk ratings, and more
• Use data-driven methods to improve, design, implement, and maintain Mercury's FCC models, including transaction monitoring, sanctions screening, and relevant models
• Develop bespoke transaction monitoring rules and sanctions screening logic designed to address Mercury's specific AML and sanctions risk
• Partner with Compliance, Product, and Data leaders to translate regulatory requirements into effective analytical frameworks
• Know how to tell stories with data, enabling people to understand the output and meaning of analytics activities in a clear, compelling manner
• Interpret analytics outputs to pinpoint which alerts, patterns, or anomalies signal genuine risk, and articulate why they matter to compliance and business stakeholders
• Develop and maintain detailed documentation on the configuration of FCC models including scenarios, thresholds, segments, tuning, false positive rules, etc., and any changes made to those configurations over time
• Evaluate and tune existing detection models and rules to reduce false positives while maintaining regulatory rigor
• Develop data-driven methods to identify new typologies, emerging risks, and evolving financial crime trends
• Partner with Model Risk Management to support validation and performance monitoring of models to ensure compliance with 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 both 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 capable of synthesizing fragmented technical, operational, and business context into a clear understanding of how models actually work, even without a complete playbook
• 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 being 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; you can explain model risk and analytics findings to both technical and non-technical stakeholders

Conditions

• The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.
• Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry.
• New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.
• Our target new hire base salary ranges for this role are the following:
• 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
• Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer.