Senior Data Scientist – Applied Machine Learning

About the role

Qualifications

• Commercial experience as a Data Scientist, Applied Scientist, Machine Learning Engineer or in a closely related role.
• Strong Python skills and experience writing maintainable, tested and production-quality code.
• Strong foundations in probability, statistics, model evaluation and machine-learning fundamentals.
• Practical experience with classification, regression, feature engineering and experimentation.
• Experience developing, deploying and maintaining machine-learning models in a cloud environment such as Databricks, AWS SageMaker, Azure ML or an equivalent platform.
• An understanding of data pipelines, feature stores, data quality, model monitoring, drift and retraining.
• Experience working across the full model lifecycle, from problem definition through to production and ongoing improvement.
• The ability to work effectively with product managers, engineers, analysts and senior business stakeholders.
• A collaborative approach to code reviews, documentation, knowledge sharing and continuous improvement.
• Good judgement about when to use a simple, explainable approach and when a more advanced technique is justified.
• Experience with generative AI, large language models or agentic AI applications.
• Experience with recommendation systems, personalisation or customer propensity modelling.
• Experience with natural language processing, time-series forecasting or financial modelling.
• Experience with MLflow, Git-based CI/CD, dbt or related data and ML engineering practices.
• Experience with R or Scala.
• Experience presenting data and model outputs using tools such as Streamlit, Power BI or Tableau.