SpaceXAI is seeking a Senior Data Analyst – Fraud & AML to modernize and strengthen financial crime detection capabilities. The role involves architecting data‑driven transaction monitoring models, building dashboards, implementing coverage assessment frameworks, and collaborating with cross‑functional teams across Compliance, Engineering, and Product. The successful candidate will lead data initiatives, support regulatory examinations, and drive continuous improvement through automation and advanced analytics.
Senior Data Analyst- Fraud & AML en SpaceXAI
Presencial - New York, NY; Palo Alto, CA
Más vacantes en SpaceXAISalary
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
- 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
Technologies
PythonSQLAI‑enabled toolingInteractive dashboardsAutomated reporting solutionsRPA solutionsCase management systemsSAR automation toolsAML detection platforms
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