Senior data scientist
- Location
- Manchester, England, United Kingdom
learning models, from problem framing and experimentation through to live deployment and monitoring. Technical depth: Apply strong statistical modelling, ML, and (where relevant) NLP / LLM techniques to solve real business problems, not just exploratory analysis. Experimentation and measurement: Design and run experiments (A / B … insights for non-technical stakeholders. Best practice: Contribute to how the wider data science function approaches tooling, methodology, and model governance. Technical Environment Languages / Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch / TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker ...