FCC Cross-Platform Data Analyst - Global

Responsibilities

• Cross-Platform Data Integration & Analysis
  • Analyze complex datasets across disparate platforms, correlating financial transaction data with non-financial signals (e.g., login patterns, device fingerprinting, Trust & Safety violations, marketplace interactions).
  • Identify patterns where platform abuse (e.g., fraud, scams, illegal goods) precedes or coincides with money laundering or terrorist financing risks.
  • Build data models that trigger alerts based on hybrid indicators (e.g., a user flagged for hate speech who suddenly receives large peer-to-peer transfers).
• Policy & Referral Process Development
  • Develop and document the logic for "Non-Financial STR Referrals," defining exactly when a Trust & Safety or Marketplace signal should trigger a financial crimes investigation.
  • Create Standard Operating Procedures (SOPs) for the intake of cross-platform referrals, ensuring they meet regulatory standards for Suspicious Transaction/Activity Reports.
  • Collaborate with Legal and Compliance leadership to calibrate risk thresholds, ensuring we capture true positives without overwhelming investigators with noise.
• Pipeline Optimization & Tooling
  • Work with Engineering and Product teams to automate the ingestion of T&S signals into the FCC case management system.
  • Design dashboards to monitor the volume, quality, and outcome of cross-platform referrals (e.g., conversion rates from T&S referral to STR filing).
  • Conduct "below-the-line" testing to tune detection scenarios and reduce false positives.
• Strategic Analytics & Insight Delivery
• Drive the design and execution of foundational FCC analytics initiatives. Go beyond routine analysis to uncover emerging risk typologies, assess control effectiveness, and provide data-driven recommendations that directly influence FCC/AML policy, operational strategies, and risk appetite.
• Take ownership of the analytics lifecycle for risk detection. Design, develop, and validate innovative data signals and features from complex, large-scale datasets to enhance our transaction monitoring, sanctions screening, and customer risk rating models.
• Architect and maintain a suite of robust dashboards and automated reports for Management Information (MI) reporting, providing senior leadership with clear visibility into key risk indicators (KRIs), control performance, and trend analysis.
• Stakeholder Collaboration
• Act as the primary liaison between the Trust & Safety, Product, and FCC Investigations teams.
• Translate complex data findings into clear policy recommendations for senior leadership.
• Provide training to investigators on how to interpret non-financial data points within a financial crime context.

• Minimum Qualifications:
  • Bachelor's degree or higher in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, or a related discipline.
  • 5+ years of hands-on experience in data analytics, data science, or a similar role, with a significant focus on the financial services, Fin Tech, or regulatory compliance/risk management sectors.
  • Advanced proficiency in SQL and demonstrable experience using Python or R for complex data manipulation, statistical analysis, and automation.
  • Proven experience working with large-scale data warehousing environments (e.g., Hive, Spark SQL, Presto) and familiarity with ETL principles.
  • Solid understanding of core AML/CFT and sanctions compliance domains (e.g., KYC/KYB, Transaction Monitoring, Sanctions Screening).
• Preferred Qualifications:
  • CAMS, CFE, or other relevant professional certification is highly desirable.
  • Deep knowledge of major AML regulatory frameworks (e.g., BSA/AML, EU AML Directives, MAS guidelines) and their practical application in a payments or e-commerce context.
  • Experience working in multi-product ecosystem (Social Media + Payments).
  • Experience in developing or validating AML models and an understanding of model risk management principles.
  • Demonstrated ability to lead complex analytical projects from conception to completion and effectively influence cross-functional stakeholders at all levels.
  • Exceptional communication and presentation skills, with the ability to translate complex data findings into clear, concise, and compelling narratives for both technical and non-technical audiences.

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