Director - Machine Learning - Financial Crime

• Lead the UK Financial Crime ML portfolio, setting technical direction and ensuring high-quality, scalable model delivery across fraud and transaction monitoring use cases
• Drive end-to-end model lifecycle ownership — from data exploration and feature engineering to deployment, monitoring, and performance optimisation
• Provide hands-on technical leadership, reviewing Python code, model design, distributed computing approaches, and architectural decisions
• Manage and develop a team of data scientists, setting standards for technical excellence, delivery discipline, and stakeholder engagement
• Engage senior stakeholders (1LOD, Compliance, Control Owners, Technology) to prioritise initiatives, resolve competing demands, and ensure regulatory alignment

• Extensive experience building and deploying machine learning models in production, with strong hands-on Python capability
• Experience with distributed computing frameworks (e.g., Spark or similar) and scalable data processing environments
• Exposure to cloud-based platforms (e.g., AWS, Azure, GCP or Databricks) and modern ML/MLOps practices
• Proven track record managing and growing high-performing data science teams, including technical mentoring and delivery accountability
• Strong stakeholder management skills, able to operate in complex, regulated environments
• experience in Financial Crime or related risk domains is advantageous

Experience in Financial Crime or related risk domains