Mercury

2 weeks ago

Financial Crimes Compliance Modeling & Analytics Manager

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Own enhancements to financial crimes compliance (FCC) detection and screening models by developing, tuning, and maintaining transaction monitoring and sanctions models. Build analytics and metrics to track the health of FCC programs, translate regulatory requirements into analytical frameworks, and refine rules to reduce false positives while maintaining rigor. Leverage SQL and data-driven methods to analyze customer and transaction behavior, identify emerging risks, and collaborate across compliance, risk strategy, product, engineering, and model risk management.

Location: San Francisco, New York, Canada, United States

Workplace: Remote

Employment Type: Full time

Job Function: Legal, Risk & Compliance

Seniority: Manager level

Key Responsibilities

•Use SQL and analytical tools to analyze customers, transactions, alerts, TM rules, risk ratings, and more.
•Improve, design, implement, and maintain FCC models, including transaction monitoring and sanctions screening models.
•Develop bespoke transaction monitoring rules and sanctions screening logic tailored to Mercury’s AML and sanctions risk.
•Partner with Compliance, Product, and Data leaders to translate regulatory requirements into analytical frameworks and metrics.
•Evaluate and tune detection models and rules to reduce false positives while maintaining regulatory rigor, including documentation and model validation support.

Pay and Benefits

Equity and Bonus:Equity

Key Requirements

•Bachelor’s degree in a quantitative field with 8+ years of experience in 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.
•Top-notch SQL skills; experience with Python or similar and familiarity with modern ML tooling (scikit-learn, XGBoost) are preferred.
•Experience developing, tuning, and maintaining machine learning or rule-based detection models, including challenging model performance and limitations.
•Strong written and verbal communication skills to explain model risk and analytics findings to technical and non-technical stakeholders.

Experience:8+ yearsFintechFinancial servicesAMLSanctionsFinancial crime detection

Education:Bachelor's in quantitative field (e.g. Computer Science, Engineering, Statistics, Mathematics)

Skills:Analytical thinkingCommunicationAttention to detailSkepticismAdaptability

Languages:English

Tech Stack:SQLPythonScikit-learnXGBoostMachine learningTransaction monitoringSanctions screening

Company Brief

Mercury

Provides banking and financial infrastructure for startups and small businesses, offering business checking accounts, payments, debit cards, venture debt integrations, and treasury services via a developer-friendly platform.

Industry: Fintech Infrastructure

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2017

Website LinkedIn

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Mercury

2 weeks ago

Financial Crimes Compliance Modeling & Analytics Manager

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: San Francisco, New York, Canada, United States

Workplace: Remote

Employment Type: Full time

Job Function: Legal, Risk & Compliance

Seniority: Manager level

Key Responsibilities

•Use SQL and analytical tools to analyze customers, transactions, alerts, TM rules, risk ratings, and more.
•Improve, design, implement, and maintain FCC models, including transaction monitoring and sanctions screening models.
•Develop bespoke transaction monitoring rules and sanctions screening logic tailored to Mercury’s AML and sanctions risk.
•Partner with Compliance, Product, and Data leaders to translate regulatory requirements into analytical frameworks and metrics.
•Evaluate and tune detection models and rules to reduce false positives while maintaining regulatory rigor, including documentation and model validation support.

Pay and Benefits

Equity and Bonus:Equity

Key Requirements

•Bachelor’s degree in a quantitative field with 8+ years of experience in 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.
•Top-notch SQL skills; experience with Python or similar and familiarity with modern ML tooling (scikit-learn, XGBoost) are preferred.
•Experience developing, tuning, and maintaining machine learning or rule-based detection models, including challenging model performance and limitations.
•Strong written and verbal communication skills to explain model risk and analytics findings to technical and non-technical stakeholders.

Experience:8+ yearsFintechFinancial servicesAMLSanctionsFinancial crime detection

Education:Bachelor's in quantitative field (e.g. Computer Science, Engineering, Statistics, Mathematics)

Skills:Analytical thinkingCommunicationAttention to detailSkepticismAdaptability

Languages:English

Tech Stack:SQLPythonScikit-learnXGBoostMachine learningTransaction monitoringSanctions screening

Company Brief

Mercury

Industry: Fintech Infrastructure

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2017

Website LinkedIn