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Aml Modeling Analyst Jobs (NOW HIRING)

Partner with client teams to assess existing AML systems, analytics tools, and monitoring models. * Develop, optimize, and test transaction monitoring rules using SQL and data analytics tools.

Partner with client teams to assess existing AML systems, analytics tools, and monitoring models. * Develop, optimize, and test transaction monitoring rules using SQL and data analytics tools.

Partner with client teams to assess existing AML systems, analytics tools, and monitoring models. * Develop, optimize, and test transaction monitoring rules using SQL and data analytics tools.

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How much do aml modeling analyst jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for aml modeling analyst in the United States is $31.53, according to ZipRecruiter salary data. Most workers in this role earn between $25.24 and $35.82 per hour, depending on experience, location, and employer.

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Infographic showing various Aml Modeling Analyst job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $65,589 per year, or $31.5 per hour.

Financial Crimes Model Analyst

Sioux Falls, SD โ€ข On-site

Other

Re-posted 5 days ago


Job description

Job Details

Job Location: SLC - Salt Lake City, UT 84111

Position Type: Full Time

Education Level: 4 Year Degree

Travel Percentage: Negligible

Job Shift: Day

Job Category: Banking

The Financial Crimes Model Analyst plays a critical role in designing, validating, and optimizing analytical models that support financial crime prevention, including fraud, AML/KYC, and sanctions monitoring. This role leverages modern data-agnostic, low/no-code analytical platforms and machine-learning tooling to operationalize robust detection logic, integrate LLM/SLM outputs responsibly, and ensure alignment with Model Risk Management (MRM) standards.

PRINCIPAL DUTIES AND RESPONSIBILITIES
  • Designs, validates, and enhances financial crime detection models across fraud, AML/KYC screening, and related domains.
  • Applies statistical techniques to evaluate and calibrate LLM/SLM outputs when used in decision-support workflows.
  • Conducts ablation studies, back testing, and reproducible experiments to ensure model stability and business impact.
  • Optimizes model and pipeline efficiency, including latency, throughput, and computational performance.
  • Develops, tracks, and interprets performance metrics.
  • Implements monitoring for drift, bias, degradation, and shifts.
  • Produces audit-ready MRM documentation, including validation plans, governance artifacts, explainability notes, and calibration reports.
  • Maintains model health dashboards and reporting for executives, governance bodies, and oversight functions.
  • Partners with internal and external data engineers and vendor partners to maintain reliable inputs and production workflows.
  • Develops SQL and Python assets for exploration, experimentation, reporting, and automated artifact generation.
  • Maintains clear and comprehensive documentation, including data dictionaries, model cards, decision logic, and workflow diagrams.
  • Works cross-functionally with engineering, product, compliance, risk, and vendor teams to deploy and maintain models.
  • Translates complex analytical concepts into accessible insights for varied technical and business audiences.

Non-Essential Functions: Performs other duties as assigned.

QualificationsEDUCATION AND/OR EXPERIENCE
  • Bachelorโ€™s degree in Statistics, Econometrics, Data Science, Mathematics, Computer Science, or a related quantitative field, required; Masterโ€™s degree, preferred.
  • 3-5 yearsโ€™ experience in model development, evaluation, monitoring, risk governance, or model lifecycle management supporting BSA/AML compliance, fraud and/or case investigation, or experience in quality assurance/control or internal audit, required.
  • Hands-on expertise in SQL and Python for analysis and rapid prototyping, required.
  • Familiarity with modern modeling techniques, or similar low/no-code platforms, and the responsible use of LLM/SLM capabilities, required.
  • Experience producing governance-grade validation or audit documentation, required.
  • Exposure to financial crime domains (AML, KYC, fraud), preferred.
  • CAMS and/or CAFP certifications, preferred.
KNOWLEDGE, SKILLS, AND ABILITIES
  • Strong understanding of supervised/unsupervised ML evaluation, calibration, drift detection, and explainability methods.
  • Knowledge of data quality domains and data lineage principles.
  • Familiarity with AI model governance concepts, including MRM standards and regulatory expectations.
  • Ability to develop and maintain dashboards and report for model health and risk indicators.
  • Knowledge of regulatory environment(s) and emerging BSA/AML and fraud trends.
  • Strong investigative, written, and oral communication skills.
  • Thorough and detail-oriented.
  • Strong commitment to ethics, and the ability to understand a variety of issues and perspectives.
  • Understanding of the banking industry, including bank partnerships with fintech companies.
  • Multitasks effectively and takes action promptly, both independently and in a team environment.
  • Handles highly confidential information with appropriate discretion, and works well in a high volume, fast paced environment.
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