Senior Data Scientist

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• Own end-to-end ML solutions - from problem framing and feature engineering to deployment, monitoring, and governance
  
• Translate business objectives into modelling strategies aligned to risk appetite and operational constraints
  
• Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent)
  
• Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production‑ready solutions
  
• Establish monitoring frameworks for performance, drift, and retraining
  
• Drive clear documentation, traceability, and governance appropriate for a regulated environment
  

This role requires someone who thinks beyond experimentation - focusing on operational impact, adoption, and long‑term model performance.

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• Proven commercial ML/Data Science delivery with measurable impact
  
• Experience taking models into production and managing performance over time
  
• Prior experience leading or mentoring Data Scientists
  
• Strong Python (pandas, numpy, scikit‑learn or similar)
  
• Strong SQL (complex joins, aggregations, analytical functions)
  
• Solid grounding in applied statistics, evaluation design, calibration, bias/fairness
  
• Experience working closely with Engineering/Data teams in production‑first environments
  
• Comfortable operating within regulated industries
  

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• AWS experience (S3, Athena/Glue, IAM, Lambda)
  
• SageMaker or equivalent ML platform experience
  
• Financial services domain knowledge (risk, fraud, affordability, payments)
  
• Experience with model explainability and governance documentation
  

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• Hybrid working model
  
• Competitive pension
  
• Additional paid leave (birthday, charity, wellbeing, life events)
  
• Employee assistance programme & Virtual GP
  
• Modern collaborative office environment