Lead Data Scientist - Anti-Money Laundering (AML) at Wise
United Kingdom
Posted
on-site · full-time · Visa sponsorship
Responsibilities:
- Design, develop and maintain AML detection systems using supervised, unsupervised and semi-supervised methods and GenAI.
- Build frameworks to measure regional control coverage and create decisioning layers to balance precision vs recall.
- Prototype and productionise models and libraries: package algorithms, deploy to staging/production and run scheduled retraining pipelines.
- Collaborate with ops, investigators and cross-functional teams to translate operational needs into automated controls and investigation tooling.
- Mentor junior data scientists and influence cross-team technical direction.
- Benchmark and optimise system performance; run experiments and provide data-driven scenario analysis.
- Create tooling for data collection, labelling and investigator-facing insights to expose typologies and red flags.
Requirements:
- Strong Python skills and proven experience building production ML services and pipelines.
- Hands-on experience with supervised and unsupervised methods, model evaluation, performance tuning and model deployment.
- Practical exposure to GenAI/LLM-driven workflows for detection or augmentation.
- Solid statistical understanding, experimentation and metrics-driven decision making.
- Product mindset: able to translate business problems into ML solutions and trade-offs.
- Experience working in cross-functional teams and communicating complex technical concepts to non-technical stakeholders.
- Experience maintaining production-grade code, automated retraining and monitoring; familiarity with scalable international systems.