About the Role
Lead the implementation and enhancement of Tookitaki's Anti-Money Laundering (AML) Suite for customer prioritization, alert disposition, and dynamic customer risk ranking. This role drives the adoption of AI/ML-powered AML solutions to improve detection accuracy and operational efficiency.
Key Responsibilities
* Lead Tookitaki AML platform implementation projects for customer risk management
* Drive customer prioritization model deployment and refinement initiatives
* Manage alert disposition workflow optimization projects using Tookitaki's capabilities
* Oversee dynamic customer risk ranking implementation and integration
* Coordinate with data science teams on machine learning model deployment
* Manage end-to-end project delivery including requirements, design, build, and deployment
* Align Tookitaki solutions with AML risk framework and regulatory requirements
* Lead change management and user adoption for AI/ML-driven AML processes
* Establish KPIs and metrics to measure platform effectiveness
* Manage vendor relationship with Tookitaki and ensure SLA compliance
* Drive continuous improvement through model retraining and feature enhancement
* Produce executive dashboards and reports on AML program effectiveness
Required Skills & Knowledge
* Tookitaki Expertise: Hands-on experience with Tookitaki AML Suite (Anti-Money Laundering, Transaction Monitoring, Customer Risk Scoring)
* AI/ML in AML: Understanding of machine learning models for anomaly detection, risk scoring
* Project Management: 8+ years leading technology projects, preferably in RegTech/AML
* Customer Risk: Experience with dynamic customer risk rating methodologies
* Alert Management: Knowledge of alert disposition workflows and optimization
* Data Analytics: Familiarity with data science concepts, feature engineering, model validation
* Regulatory Compliance: Strong knowledge of MAS AML/CFT requirements
* Integration: Experience integrating AML platforms with core banking, KYC systems
Preferred Qualifications
* PMP, Agile, or similar project management certification
* CAMS, CFE, or equivalent AML/fraud certification
* Background in data science or analytics
* Experience with Python, R, or SQL for data analysis
* Knowledge of model risk management (MRM) frameworks
* Previous experience implementing AI/ML solutions in banking
* Familiarity with graph analytics and network analysis for AML
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