Senior AML Modeling Engineer (Payments & Crypto)

About the role

This position focuses on developing and optimizing anti-money laundering (AML) risk models for both fiat and cryptocurrency transactions. The work involves creating rule-based engines and machine learning solutions to detect complex money laundering patterns. A key aspect is the design of transaction monitoring strategies, including anomaly detection and fund flow analysis, to strengthen the platform's risk control and compliance.

The role requires analyzing on-chain data to trace fund movements and identify high-risk address behaviors. This includes building user risk scoring systems that integrate KYC, transactional, and blockchain data. The successful candidate will continuously work to improve model performance, aiming to reduce false positives and enhance the efficiency of investigations.

Success in this role means effectively deploying AML models for transaction monitoring, risk scoring, and investigation support. It involves a deep understanding of common AML typologies such as layering and smurfing, and applying this knowledge to build robust detection systems that protect the platform and its users.

The annual salary for this role ranges from $136,000 to $230,000.

Skills that matter here

• Python: This role requires strong proficiency in Python for data analysis and building AML models.
• SQL: SQL is essential for data analysis and querying the necessary transactional and blockchain data.
• machine learning: Machine learning models like XGBoost and LightGBM are used to enhance AML detection capabilities and reduce false positives.
• AML modeling: The core of this role involves developing and optimizing AML risk models, including rule-based engines and machine learning approaches.
• data analysis: Data analysis skills are critical for interpreting on-chain and transactional data to identify money laundering patterns.

Who this role suits

• You have at least five years of experience specifically in AML or risk modeling.
• You have a proven track record of deploying AML models from start to finish.
• You possess a solid understanding of various money laundering methods and typologies.
• You are adept at using machine learning techniques to solve real-world problems.

From the employer

• Develop and optimize AML risk models (rule-based engines + machine learning)
• Design transaction monitoring strategies (e.g., anomaly detection, transaction structuring, fund flow analysis)
• Analyze on-chain data to track fund movements and identify high-risk address behaviors
• Build user risk scoring systems integrating KYC, transactional, and blockchain data
• Continuously improve model performance, reduce false positives, and enhance investigation efficiency

• 5+ years of experience in AML / risk modeling (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)