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Mid-level metro role at a reputable fintech but niche AML specialization reduces applicant density.
Requires domain-specific AML and regulatory experience, limiting transferability across industries.
Mandatory 4+ years plus required SQL/Python/PySpark and AML regulatory expertise meaningfully narrows candidates.
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Lead design and development of advanced AML monitoring models focusing on behaviour-based and risk-segmented controls.
Optimize AML detection framework using statistical methods to balance detection effectiveness and operational productivity.
Maintain audit-ready documentation and contribute strategically to AML analytics innovation and roadmap.
Minimum 4 years experience in data analytics, preferably in financial crime or risk management.
Proficiency in SQL and Python including libraries such as Pandas and PySpark for handling large datasets.
Experience applying optimization algorithms and statistical techniques to real-world monitoring problems.
Strong understanding of financial crime regulatory frameworks applicable to transaction monitoring.
Experienced technical leader capable of architecting sophisticated AML monitoring models beyond simple transaction triggers.
Skilled in translating AML typologies and risk policies into actionable data-driven monitoring logic.
Effective communicator able to explain complex statistical models and optimizations to diverse stakeholders including non-technical audiences.