Lead Project Manager – Tookitaki AML Platform

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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