Aml Analyst

Role & responsibilities

• AI/ML Project Delivery: Drive the end-to-end implementation of Artificial Intelligence and Machine Learning models for predictive risk scoring and advanced anomaly detection.
• Rule Automation: Design, test, and implement automated transaction monitoring rules to reduce manual intervention and streamline compliance workflows.
• Threshold Optimization: Conduct regular tuning, statistical analysis, and optimization of system thresholds to minimize false positives while maintaining high detection rates.
• Data Reconciliation: Establish robust data reconciliation frameworks to ensure seamless data integrity and completeness between core banking systems and AML platforms.
• Cross-Functional Collaboration: Partner with Data Science, IT, and Compliance Operations to translate complex analytical models into production-ready AML tools.
• Testing & UAT: Conduct User Acceptance Testing (UAT) for rule engines, reconciliation workflows, and AI/ML model deployments.
• Documentation & Governance: Maintain rigorous documentation for threshold changes, model validation reports, and automated logic to meet audit and regulatory expectations.
• Strong AML compliance knowledge combined with data analytics and technical project management skills.
• Proven experience implementing AI/ML models and automating transaction monitoring rules.
• Experience performing complex data reconciliations between core platforms and AML systems.
• Proficiency in statistical analysis for tuning system thresholds and reducing false positives.
• Exceptional cross-functional communication to bridge data science, IT, and compliance operations.
• Experience drafting detailed technical documentation, including BRDs and FSDs.
• Ability to manage end-to-end UAT cycles for compliance software and automated workflows.
• Strict adherence to global anti-financial crime regulations and audit documentation standards.