Lead Data Scientist - Servicing

Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

We’re looking for a Lead AI Data Scientist to join our Servicing team in London. This role is a unique opportunity to work on the intelligence system at the core of our operational handling work. You will help automate components of our operational systems and build solutions that reduce financial crime risk. What you build will have a direct impact on Wise’s mission and millions of our customers.

The Servicing team offers an exciting environment for applying cutting-edge Generative AI solutions. This team is dedicated to enhancing our financial crime mitigation operations through tooling and automation, aiming to streamline reviews and simplify the work of our operations staff. A core focus involves analyzing and automating significant parts of our operational workflows. Furthermore, the team develops LLM-based tools to assist crime prevention teams in deflecting demand. The successful candidate will have the chance to directly contribute to Wise's mission by tackling these challenges and developing a comprehensive testing suite for our solutions.

Responsibilities

• End-to-End Automation: Lead the development and deployment of AI models designed to augment operational workflows, specifically targeting the automation of case comments, red flag generation, final review summaries, and data labeling.
• Full-Stack Deployment: Take ownership of the production pipeline by writing and deploying production-ready Python services. You must be willing to bypass engineering bottlenecks to ship value quickly while maintaining code quality.
• Human-in-the-Loop Architecture: Design systems where AI provides recommendations and drafts, ensuring human operators retain the final decision-making authority for critical financial crime mitigation assessments.
• Rigorous Testing & Governance: Establish comprehensive testing frameworks (e.g., shadow mode, A/B testing) for production environments and act as the technical liaison with Compliance to ensure all models meet regulatory standards prior to launch.
• Strategic Demand Deflection: Go beyond ticket handling by analyzing upstream data to create strategies that deflect financial crime attempts before they reach the operations team, effectively reducing manual workload.
• Mentorship & Leadership: Lead and grow other Junior Data Scientists, fostering a product-focused mindset and guiding them through complex technical implementations and architectural decisions.

A bit about you

• Experience implementing, training, testing and evaluating performance of Machine Learning systems.
• Strong Python knowledge. A big plus for proven familiarity and experience with OOP principles.
• Knowledge and experience developing Unsupervised Learning methods.
• Experience with statistical analysis, and ability to produce well-designed experiments.

Additional information

• Hands-on experience training Neural Network models and deploying them into production.
• Familiarity with automating operational processes via technical solutions, for example Large Language Models.
• Experience implementing fine-tuning, reinforced learning alignment and evaluation techniques within an LLM training pipeline.
• Familiarity with agentic frameworks such as LangGraph or similar.
• Willingness to get hands dirty reading many historical operational cases.

For everyone, everywhere. We’re people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We’re proud to have a truly international team, and we celebrate our differences. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.