Senior Data Analyst- Fraud & AML en SpaceXAI

Presencial - New York, NY; Palo Alto, CA

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SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. We operate with a flat organizational structure, expecting all employees to be hands‑on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important, as are strong communication skills. We are looking for a Senior Data Scientist to join our Compliance Program and play a pivotal role in modernizing and strengthening our financial crime detection capabilities, architecting data‑driven transaction monitoring models, coverage assessment frameworks, and advanced analytics solutions to support BSA/AML regulatory compliance.

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
  • 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

Technologies

PythonSQLAI‑enabled toolinginteractive dashboardsautomated reporting solutionstransaction monitoring frameworksSAR filing metricsSAR narrative generator tools

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