# Financial Crimes Compliance Modeling & Analytics Manager

**Company**: Mercury
**Location**: San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
**Experience**: senior
**Job type**: full-time
**Salary**: 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
**Category**: Finance
**Industry**: Finance

**Apply**: https://job-boards.greenhouse.io/mercury/jobs/6111066004?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_45ec098a-b5e

## Description

Mercury is building a complete finance stack for startups, simplifying entrepreneurs' and business owners' financial lives while ensuring protection from bad actors and harmful activities.

As Financial Crimes Compliance Modeling & Analytics Manager, you'll drive enhancements to Mercury's financial crimes compliance (FCC) detection and screening models and improve the overall FCC framework.

## 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

- 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

- 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

## 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

- 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

- Experience developing, tuning, and maintaining machine learning or rule-based detection models

- 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

- 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

## Benefits

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

## Skills

### Required
- SQL
- Python
- machine learning
- data analytics
- AML
- Sanctions

### Nice to have
- scikit-learn
- XGBoost

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/mercury/jobs/6111066004?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)