Financial Crimes Compliance Modeling & Analytics Manager

About the role

In this position, you will be responsible for improving Mercury's financial crimes compliance detection models. Your work will involve conducting in-depth analyses of customer transactions and developing tailored monitoring rules to address specific risks.

Collaboration is key, as you will partner with various teams to translate regulatory requirements into effective analytical frameworks. Success in this role means effectively identifying risks and communicating insights clearly to both technical and non-technical stakeholders.

The salary range for this role is competitive, with specific figures depending on geographic location and experience.

Skills that matter here

• SQL: You will use SQL for conducting detailed analyses of customer transactions and compliance models.
• Python: Experience with Python is preferred for developing and maintaining detection models.
• machine learning: You will apply machine learning techniques to enhance detection models and improve operational efficiencies.
• data analytics: Strong data analytics skills are essential for interpreting outputs and identifying risks.

Who this role suits

• You have a strong background in quantitative fields and extensive experience in data analytics.
• You are comfortable navigating ambiguity and can synthesize complex information into clear insights.
• You possess a solution-oriented mindset and are adaptable in a fast-paced environment.
• You are detail-oriented with strong communication skills, capable of explaining complex findings to diverse audiences.

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.