xAI is seeking a Senior Data Analyst- Fraud & AML to modernize and strengthen financial crime detection. The role involves building and optimizing AML/fraud models, creating performance dashboards, architecting transaction monitoring coverage frameworks, and supporting regulatory examinations. Collaboration across compliance, engineering, and product teams is essential, with a focus on data‑driven solutions and advanced analytics.
Salary
USD 148,000 - 220,000
Requirements
Skills
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
Demonstrated ability to translate complex regulatory requirements into actionable data solutions and present findings to senior leadership and regulators
Certified Anti-Money Laundering Specialist (CAMS) or equivalent compliance certification is strongly preferred
Experience leading cross‑functional initiatives involving Engineering, Legal, Product Compliance, and external consulting partners
Background in building internal case management systems, SAR automation tools, or RPA solutions
Familiarity with AML detection platforms
Track record of delivering measurable impact (e.g., reduced case volumes, improved detection of high‑risk activity, increased operational efficiency)
Responsibilities
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
Build and maintain interactive performance dashboards and automated reporting solutions that track key risk, productivity, and capacity metrics for senior leadership and regulators
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
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
Embed data science best practices into product launches and feature rollouts to proactively identify and close monitoring coverage gaps
Support regulatory examinations (e.g., NYDFS Part 504) by preparing analytical documentation, third‑party validation materials, and executive certification packages
Drive continuous improvement of compliance operations through automation, process optimization, and advanced analytics