Lead Data Scientist – AML

Overview

In this AML Risk role, you will develop detection systems that combine unsupervised, semi-supervised, and supervised learning with GenAI to combat financial crime at scale. You work across functions to deploy global, production‑grade models and provide insight into red flags and typologies. You will mentor juniors, optimize performance, and ensure production readiness of deployable ML components. This role combines cutting‑edge ML with operational processes to support Wise’s growing customer base.

Responsibilities

• Develop AML detection controls using mixed learning approaches and GenAI
• Build frameworks to prove regional control coverage
• Collaborate with cross-functional teams to solve global AML problems
• Mentor junior team members on technical and non‑technical skills
• Evaluate systems against benchmarks and balance precision and recall
• Design and manage projects leveraging operational capacity for model improvement
• Package algorithms for production and automate retraining pipelines
• Provide investigations insights on red flags and typologies

Key requirements

• Experience building and evaluating ML systems (training, testing, performance)
• Strong Python knowledge; good OOP familiarity
• Experience with statistical analysis and designing experiments
• Product-minded, able to work independently in cross-functional environments
• Effective communication with non-technical stakeholders
• Strong problem solving and requirements refinement skills

• communication
• mentoring
• collaboration
• Python
• ML model development and evaluation
• GenAI / large language models (LLMs) familiarity (nice to have)

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