Lead Data Scientist – AML

Overview

In this role, you will help build and refine Wise’s AML risk detection systems using a blend of unsupervised, semi-supervised, supervised learning and GenAI. You’ll work across functions to scale controls for a global user base and mentor teammates. You’ll evaluate models against benchmarks and shape automated, data-driven decisioning to reduce financial crime. This is a hands-on, impact-driven role in a fast-paced fintech environment.

Responsibilities

• Develop AML detection controls using mixed ML approaches and GenAI
• Create regional controls coverage frameworks
• Collaborate across functions to solve AML problems at global scale
• Mentor junior team members on technical and soft skills
• Evaluate AML systems against internal/external benchmarks and optimize precision/recall
• Develop data-driven insights for outcome scenarios
• Refine operational processes with automation and feedback loops
• Package algorithms for production and manage data pipelines for retraining
• Provide investigators with actionable insights through systems and red-flag typologies

Key requirements

• Experience implementing, training, testing and evaluating performance of ML systems
• Strong Python knowledge (OOP is a plus)
• Experience with statistical analysis and well-designed experiments
• Product mindset with ability to work independently in cross-functional settings
• Excellent communication skills to convey technical concepts to non-technical stakeholders
• Strong problem-solving ability to refine statements and devise solutions

• Cross-functional collaboration
• Effective communication
• Independent working style
• Machine Learning system development
• Python programming
• Statistical analysis and experimental design

…