Financial Crimes Risk Signal Analyst

The Financial Crimes Risk Signal Analyst specializes in evaluating alerting signals, data inputs, and risk indicators used across fraud and BSA/AML/OFAC detection systems. The role ensures signals are performing as intended, validates data quality, and supports reporting that informs model and rule refinement across financial crime programs.

PRINCIPAL DUTIES AND RESPONSIBILITIESResearches and validates risk signals used in transaction monitoring, fraud scoring, and rule-based alerting.

Ingests, cleanses, transforms, and validates data from diverse sources to support analytics, dashboards, and enabled models.

Supports end-to-end life cycle of alerting quality and effectiveness for Financial Crimes Programs.

Supports data quality dashboards, scorecards, and alerting mechanisms.

Conducts data quality assessments, contributes to root-cause analysis, and participates in remediation planning.

Assists in development of KRIs and KPIs such as detection efficiency, signal precision, and false-positive ratios.

Maintains structured documentation supporting compliance, audit, model, and financial crimes risk governance.

Collaborates with Compliance, Enterprise Data, and Risk teams to refine signal thresholds, rule logic, and detection coverage.

Translates complex analytical concepts into accessible insights for varied technical and business audiences.

Performs other duties as assigned.

EDUCATION AND/OR EXPERIENCE Bachelor’s degree in Analytics, Information Systems, Finance, Criminal Justice, or related field, required.
3-5 years’ experience in fraud/AML analytics, risk signal validation, or operational risk monitoring, required.
3-5 years’ experience in BSA/AML compliance, fraud and/or case investigation, or experience in quality assurance/control or internal audit, required

Experience with data-driven roles involving large datasets, preferred.

Experience producing governance-grade validation or audit documentation, preferred.

Exposure to financial crime domains (AML, KYC, fraud), preferred.

CAMS and/or CAFP certifications, preferred.

KNOWLEDGE, SKILLS, AND ABILITIES Strong analytical and conceptual thinking skills, with the ability to assess risk signals, indicators, and detection logic.

Proficiency with SQL, PowerBI and comfort navigating transaction-level datasets.

Ability to translate signal performance issues into actionable insights.

Understanding of AML/fraud regulatory principles and risk detection concepts.

Familiarity with visualization tools for presenting findings to non-technical stakeholders.

High attention to detail, with strong documentation and audit readiness standards.

Knowledge of data quality domains and data lineage principles.

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.

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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