Head of Data Science

📋 Description Prioritise which opportunities have the biggest impact.. Build a value-based use-case backlog Personally deliver the first system end to end: the analysis and back-test, the features, the Operate what you deploy. Own monitoring, retraining, drift response, incident handling and rollback Work across both traditional ML and agentic systems, and be honest about which a problem actually Build and lead the team — hire senior data scientists embedded in value areas and machine learning Establish the production stack alongside Data Platform and Engineering: reproducible training data 🎯 Requirements Experienced leading data science or ML teams that own systems in production, with deployments that Hands-on now, not formerly. Your first quarters are spent writing SQL and Python, engineering Experienced across both traditional ML and agentic systems, and clear about how they differ in Practised at running live systems rather than just launching them — monitoring, retraining Pragmatic about method: happy to argue for rules or heuristics where they capture most of the Comfortable with an undefined starting point. There's a long list of candidate use cases and a 🎁 Benefits Remote work options (digital-first company) Unlimited holidays 4 months paid family leave regardless of gender Annual learning fund and personal development opportunities Exposure to new challenges and internal/external training Inclusive and collaborative culture