• 5+ years of experience in AML / risk modeling (mandatory)
• mandatory
• Proven end-to-end experience in deploying AML models (e.g., transaction monitoring, risk scoring, investigation support)
• Strong proficiency in Python and SQL for data analysis and modeling
• Solid understanding of common AML typologies (e.g., layering, smurfing, cash-out)
• Hands-on experience with machine learning models (e.g., XGBoost, LightGBM)
• Experience in crypto / blockchain analytics
• Familiarity with on-chain analytics tools (e.g., Chainalysis, Elliptic)
• Background in AML within payments, banking, or crypto industries
• Experience with graph analytics or real-time risk systems
• Goals
• Enhance detection capabilities for complex money laundering activities
• Reduce false positives and improve investigation efficiency
• Proactively identify high-risk fund flows