Lead Data Scientist – Anti-Money Laundering (AML)

Overview

In this Lead Data Scientist role, you will shape Wise’s global AML capabilities by building AI-driven financial crime detection systems. You’ll work within the AML Risk team to deploy unsupervised, semi-supervised and supervised models, including GenAI, to scale detection across a diverse international user base. You will mentor juniors, collaborate with cross-functional teams, and translate data-driven insights into practical controls and processes. This is an impact-driven position at a fast-growing fintech that emphasizes safety, scalability, and responsible innovation.

Pay / Benefits

• Stock options
• Hybrid working model
• Annual personal development budget
• Visa and relocation support

Responsibilities

• Develop AML detection controls using a mix of unsupervised, semi-supervised and supervised learning with GenAI
• Create frameworks to prove regional controls coverage
• Develop technologies to serve Wise’s international user base
• Mentor junior team members on technical and non-technical skills
• Evaluate AML systems against benchmarks and optimize precision-recall trade-offs
• Provide data-driven insights on potential outcomes under various scenarios
• Collaborate with operational teams to refine processes and automate feedback
• Package algorithms into deployable libraries and manage production-ready Python services
• Oversee data gathering and model retraining via automated pipelines
• Design insights for investigators on red flags and typologies in profiles/transactions

Key requirements

• Experience building, training, testing and evaluating ML systems
• Strong Python knowledge; familiarity with OOP is a plus
• Experience with statistical analysis and well-designed experiments
• Product mindset and ability to work independently in cross-functional settings
• Good communication skills for non-technical audiences
• Strong problem-solving abilities to refine problem statements and solutions

• cross-functional collaboration
• strong communication
• problem solving
• Machine Learning system development
• Python programming
• statistical analysis

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