Director of Data Science - Fincrime

We’re looking for a visionary Director of Data Science to lead our Financial Crime team across our key hubs in London and Tallinn. This is a pivotal role for Wise, offering a unique opportunity to delve deep into the intricate world of financial transactions, understanding the sophisticated mechanisms we employ to detect and prevent Financial Crime. As the Director of Data Science, you will provide technical leadership and mentorship to a highly skilled team of (25) data scientists, tackling complex, global-scale challenges inherent in the fight against Financial Crime. FinCrime at Wise is made up of 5 Squads: Fraud, Anti-Money Laundering, Onboarding & KYC, Screening and Funds & AUP. You’ll be an instrumental figure in safeguarding our platform and customers, ensuring robust risk mitigation while simultaneously delivering the seamless, trustworthy service our users expect. Your expertise will shape the strategic direction and drive the adoption of cutting-edge artificial intelligence (AI) and machine learning (ML) technologies. These innovations will be crucial in building advanced Financial Crime detection and prevention systems, ensuring the secure and uninterrupted financial services our customers rely on. What you and your team build will have a direct impact on Wise’s mission and millions of our customers worldwide. What You’ll Do • Cross-Functional Collaboration & Customer Impact: Partner strategically with Product, Engineering, and Operations leaders, as well as Privacy and Compliance teams, to embed data science effectively into product roadmaps. This includes ensuring our solutions maximise customer and business value while rigorously addressing compliance and privacy requirements, with a strong focus on tangible customer solutions and measurable impact. • Technical Leadership & Innovation: Define and drive the technical vision for our FinCrime Data Science team, encompassing comprehensive data strategies, large-scale model optimisation, and the adoption of next-generation AI/ML architectures (e.g., transformers, agentic AI, computer vision). Shape the research agenda, evaluate emerging technologies, and foster a culture of experimentation and continuous learning to ensure cutting-edge solutions and maintain technical standards, model governance, and best practices. • Delivery Excellence & Operationalisation: Establish and oversee scalable deployment strategies, robust MLOps practices, model monitoring, A/B testing, and performance tracking to ensure production success. Drive process improvements that accelerate iteration speed and delivery quality across all data science projects. • Team Development & Mentorship: Lead, mentor, and grow our talented data scientists, building technical capabilities across the team, fostering career development, and promoting knowledge sharing on cutting-edge technologies and methodologies.