Senior Data Analyst- Fraud & Aml

xAI xAI · AI Frontier · New York, NY +1 · Safety

Senior Data Scientist role focused on modernizing and strengthening financial crime detection capabilities by architecting, building, and optimizing data-driven transaction monitoring models, coverage assessment frameworks, and advanced analytics solutions to support BSA/AML regulatory compliance. The role involves working with Python, SQL, and AI-enabled tooling, partnering with a Compliance Machine Learning team, and supporting regulatory examinations.

What you'd actually do

  1. Design, develop, and enhance AML and fraud models, rules, and heuristics using Python, SQL, and AI-enabled tooling; partner with the Compliance Machine Learning team on model reviews to improve detection rates and reduce false positives.
  2. Build and maintain interactive performance dashboards and automated reporting solutions that track key risk, productivity, and capacity metrics for senior leadership and regulators.
  3. Architect and implement enterprise-wide Transaction Monitoring Coverage Assessment frameworks, including standardized methodologies for gap identification, root-cause analysis, remediation planning, and ongoing sustainability monitoring.
  4. Lead complex data initiatives, including extraction of SAR filing metrics with product-level breakdowns and development of jurisdiction- and typology-specific SAR narrative generator tools.
  5. Embed data science best practices into product launches and feature rollouts to proactively identify and close monitoring coverage gaps.

Skills

Required

  • Python
  • SQL
  • data science
  • advanced analytics
  • fraud detection
  • financial crime compliance
  • transaction monitoring models
  • coverage assessment frameworks
  • BSA/AML regulations
  • suspicious activity reporting
  • customer due diligence
  • sanctions screening
  • model risk management

Nice to have

  • AI-enabled tooling
  • model reviews
  • performance dashboards
  • automated reporting solutions
  • SAR filing metrics
  • SAR narrative generator tools
  • regulatory examinations (e.g., NYDFS Part 504)
  • CAMS certification
  • cross-functional initiatives
  • internal case management systems
  • SAR automation tools
  • RPA solutions
  • AML detection platforms

What the JD emphasized

  • 7+ years of hands-on data science / advanced analytics experience in financial services, with at least 4 years focused on fraud and financial crime compliance
  • Master’s degree (or higher) in Applied Mathematics, Statistics, Data Science, Actuarial Science, or a related quantitative field
  • Proven track record of building and optimizing transaction monitoring models, coverage frameworks, or compliance analytics programs in a regulated environment (fintech, bank, or payment company preferred)
  • Deep understanding of BSA/AML regulations, suspicious activity reporting, customer due diligence, sanctions screening, and model risk management principles
  • Certified Anti-Money Laundering Specialist (CAMS) or equivalent compliance certification is strongly preferred

Other signals

  • design, develop, and enhance AML and fraud models, rules, and heuristics using Python, SQL, and AI-enabled tooling
  • partner with the Compliance Machine Learning team on model reviews to improve detection rates and reduce false positives
  • architect and implement enterprise-wide Transaction Monitoring Coverage Assessment frameworks
  • Lead complex data initiatives, including extraction of SAR filing metrics with product-level breakdowns and development of jurisdiction- and typology-specific SAR narrative generator tools