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