About the Role
Serve as the Lead Functional Business Analyst for Tookitaki AML platform implementations focusing on customer prioritization, alert disposition, and dynamic customer risk ranking. This role combines deep AML domain expertise with data-driven insights to optimize financial crime detection and investigation processes.
Key Responsibilities
• Lead business analysis for Tookitaki AML Suite implementations
• Design customer prioritization frameworks using AI/ML risk scoring models
• Develop alert disposition strategies and workflow optimization recommendations
• Define requirements for dynamic customer risk ranking algorithms
• Analyze customer behavior patterns and risk indicators for model input
• Create business rules for customer segmentation and risk scoring
• Document functional requirements for machine learning model features
• Design user interfaces for AML analysts and investigators
• Support model validation and performance monitoring activities
• Analyze alert quality metrics and recommend model tuning parameters
• Create comprehensive BRDs, process flows, and data mapping documents
• Develop training materials and support user adoption
• Collaborate with data scientists on feature engineering requirements
Required Skills & Knowledge
• Tookitaki Expertise: Hands-on experience with Tookitaki AML Suite modules (Transaction Monitoring, Customer Risk Scoring, Alert Management)
• AI/ML Concepts: Understanding of supervised/unsupervised learning, feature engineering, model performance metrics
• Customer Risk: Expertise in customer risk rating methodologies and dynamic risk assessment
• Alert Analytics: Experience analyzing alert patterns, false positive rates, investigation outcomes
• Business Analysis: 8+ years as FBA in banking, preferably in Risk/Compliance
• Data Proficiency: Strong SQL skills, experience with data visualization tools (Tableau, Power BI)
• AML Domain: Deep knowledge of transaction monitoring, customer due diligence, suspicious activity detection
• Regulatory: Understanding of MAS AML/CFT guidelines and risk-based approach
Preferred Qualifications
• CAMS, CGSS, or equivalent certification
• Background in data analytics, statistics, or computer science
• Experience with Python or R for data analysis
• Knowledge of graph databases and network analysis
• Familiarity with feature stores and MLOps practices
• Experience with agile/scrum methodologies
• Previous implementation of AI-powered AML solutions
• Understanding of explainable AI (XAI) in financial crime context
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