Senior Data Science Lead – AML Risk

Overview

In this Data Science Lead role, you will help scale Wise’s AML risk capabilities by leading a team and delivering ML-based detection solutions. You’ll bridge product and engineering to build global, scalable controls and models, with a focus on unsupervised, supervised, and GenAI-driven detection. You will mentor specialists, shape the data science roadmap, and work with cross-functional teams to reduce financial crime risk while enabling growth. This role offers impact across Wise’s international customer base and product space.

Responsibilities

• Develop AML detection controls using a mix of unsupervised, semi-supervised, supervised learning and GenAI
• Create regional coverage frameworks for controls
• Build technologies serving Wise’s diverse international user base
• Assemble and mentor a high-performing data science team
• Collaborate with product managers and engineering leads on staffing and development
• Evaluate AML systems against benchmarks and optimize precision/recall
• Provide data-driven insights on outcomes under various scenarios
• Collaborate with operations to refine processes and integrate feedback into automation
• Package algorithms for production deployment and manage pipelines for retraining
• Maintain production-grade Python services

Key requirements

• Experience building, training, testing and evaluating ML systems
• Strong Python skills; familiarity with OOP architecture
• Background in statistical analysis and experimental design
• Product mindset with ability to work in cross-functional settings
• Good communication skills to explain technical concepts to non-technical audiences
• Strong problem-solving ability to formulate and solve problems

• communication
• problem solving
• independence in cross-functional environments
• Machine Learning system development
• GenAI familiarity (advantageous)
• Statistical analysis and experimental design

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