Financial Crimes Compliance Modeling & Analytics Manager

Financial Crimes Compliance Modeling & Analytics Manager

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Mercury is building a complete finance stack for startups. We work hard to create the easiest and safest banking
* experience possible to simplify entrepreneurs' and business owners’ financial lives. The challenge is to do so while ensuring we protect Mercury, customers and the broader financial ecosystem from bad actors and harmful, illegal or unauthorized activities.
* Mercury*, while not a bank itself, is an important part of the U.S. financial ecosystem. Mercury provides banking services to ambitious entrepreneurs, and in so doing, must play a part in also working to root out bad actors and prevent them from accessing or abusing the U.S. financial system.
The BSA/AML & Sanctions compliance team serves as the oversight function for the overall AML & Sanctions program. As a FCC Modeling and Analytics Manager, you’ll help drive enhancements to our financial crimes compliance (FCC) detection models and help improve Mercury’s overall FCC framework. The Manager will play a critical role in developing, tuning, and maintaining Mercury’s transaction monitoring (TM) and Sanctions models.

The Manager will also create the analytics and metrics to track the health of FCC programs and develop executive-level reporting.
This technical position requires a strong analytical background and strong FCC subject‑matter expertise. The Manager of Modeling and Analytics will collaborate closely with risk strategy, engineering, and compliance teams.

* Mercury is a fintech company, not an FDIC‑insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

• 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, customer risk scoring, and relevant alert models.
• Develop bespoke transaction monitoring rules designed to address Mercury’s specific AML 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.
• Understand both the what and the why of FCC analytics – what are we looking for and why does it matter.
• Develop and maintain detailed documentation on the configuration of FCC models – scenarios, thresholds, segments, tuning, etc. – and any changes made to those configurations over time.
• Assist with evaluating and tuning 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.

• 12+ years of experience conducting in-depth data analytics.
• Deep understanding of the FCC/AML fundamentals, including both principles and regulations.
• Outstanding skills with standard analytical tools. Top‑notch SQL skills are required; experience with Python, R or similar is preferred.
• Strong ability to turn data and analyses into compelling narratives.
• 7+ years of experience working in FCC or AML‑related analytics roles.
• Experience identifying ways to improve both data‑related and operational efficiencies.
• Have the technical writing skills to translate code into plain English and vice versa.

The total rewards package at Mercury includes base salary, equity (stock options), 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.