Senior Data Science Lead – AML Risk

Overview

In this role, you will lead and grow Wise’s AML Risk Data Science team, building scalable ML-based detection systems to combat financial crime globally. You work closely with product and engineering to implement unsupervised, supervised, and GenAI-enhanced controls across Wise’s licenses. You’ll design evaluation frameworks, optimize precision-recall trade-offs, and mentor specialists to deliver high-impact risk solutions. The role offers visible impact on customer safety and the company’s mission to move money securely. This is a chance to shape AI-driven risk programs at scale in a fast-growing fintech.

Responsibilities

• Develop AML detection systems using unsupervised, semi-supervised, supervised learning and GenAI
• Create regional coverage frameworks for controls
• Develop technologies to support Wise’s diverse international user base
• Build and mentor a high-performing data science team
• Collaborate with product managers and engineering leads on staffing and resourcing
• Evaluate AML systems against benchmarks and optimize decisioning layers for precision/recall
• Provide data-driven insights on potential outcomes under various scenarios
• Collaborate with operations to refine processes and automate model improvements
• Package algorithms for production deployment and manage data pipelines for retraining
• Maintain production-grade Python services and deploy ML solutions

Key requirements

• Experience building and evaluating ML systems (training, testing, performance)
• Strong Python skills; familiarity with OOP is a plus
• Experience with statistical analysis and designing experiments
• Product-minded with ability to work cross-functionally
• Strong communication skills to translate technical concepts to non-technical stakeholders
• Problem solving and capability to refine problem statements

• cross-functional collaboration
• communication
• independence
• Machine Learning system development
• Python programming
• Statistical analysis

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