Head of Financial Crime Prevention Model Analytics (EMEA)
On-siteBengaluru, Karnataka, India or Pune, Maharashtra, India
Job Summary
Monitor Transaction Monitoring, Customer Screening, and Payment Screening performance to calibrate scenarios, rules, and thresholds while reducing false positives. Own ongoing calibration of financial crime detection solutions and partner with Technology, Data, and vendor teams to optimize implementation and governance. Oversee data quality, integrity, and lineage for monitoring systems; validate completeness, accuracy, and timeliness of screening data. Manage sanctions, PEP, and adverse media list governance, including onboarding, maintenance, and lifecycle configuration. Produce management information on risk coverage and detection performance to support governance forums and regulatory examinations. Lead a high-performing FCP Model Analytics function, establishing methodologies and fostering evidence-based decision-making across emerging typologies and AI-enabled detection techniques.
Required Qualifications
- Significant experience in financial crime analytics
- Strong understanding of financial crime typologies and detection methodologies
- Strong analytical, statistical and data interpretation skills
- Experience designing performance metrics, model governance and management information
- Understanding of data quality, data governance, data lineage and AI model governance principles
- Ability to translate complex analytical findings into practical, risk-based recommendations for senior stakeholders
- Strong stakeholder management skills
- Ability to work effectively with second-line Financial Crime Risk and Controls teams
Desired Qualifications
- Experience operating within wholesale, institutional, brokerage, trading, payments or capital markets environments
- Experience supporting model validation, regulatory reviews, audit examinations or financial crime technology programs
- Knowledge of AI, machine learning, SQL, Python, data visualization or other advanced analytics techniques
- Experience with financial crime technology and data providers such as NICE Actimize, CGI Hotscan360, Dow Jones Risk & Compliance, LSEG World-Check and WorkFusion
- Relevant professional qualification, degree or equivalent experience in financial crime, data analytics, risk management, computer science, data science, statistics, mathematics, engineering, economics or another STEM-related discipline
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