About the role
Lead global AML risk analytics and modeling for a major financial group, driving advanced analytics to detect and prevent money-laundering activities while ensuring regulatory compliance.
BankingOnsite
Key Responsibilities
- Develop and enhance AML risk models and analytics frameworks across all business lines and jurisdictions
- Lead a global team of data scientists, quants, and compliance professionals
- Partner with regulators, internal audit, and senior management to ensure model governance and regulatory adherence
- Drive innovation in machine-learning and AI techniques for transaction monitoring and customer risk profiling
- Oversee model validation, performance testing, and continuous improvement cycles
- Present risk insights and model outcomes to executive committees and board-level stakeholders
Requirements
- 12+ years of experience in AML, financial crime risk analytics, or related quantitative compliance roles
- Proven track record of building and deploying statistical or machine-learning models in a financial crime context
- Deep knowledge of global AML/BSA, FATF, and OFAC regulations
- Advanced degree in Finance, Economics, Mathematics, Statistics, Computer Science, or related quantitative field
- Strong leadership experience managing cross-functional and geographically distributed teams
- Expertise in Python, R, SQL, SAS, or similar analytics and data-science toolkits
- Experience with big-data platforms and cloud technologies for scalable risk analytics
- Excellent communication skills with ability to translate complex analytics into actionable business and regulatory insights
- Professional certifications such as CAMS, CFA, or FRM strongly preferred
- Willingness to travel internationally up to 25%