Data Scientist

Datatech Analytics

Data SciencemidReading, England, UKhybridfulltimeFinancial Services and BankingPythonpandasNumPyscikit-learnregressionclassificationclusteringtime seriesposted 15 Sep
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Data Scientist

Berkshire · Hybrid · £70,000 + benefits

Financial Services

A good opportunity for a Data Scientist who wants to build things that actually get used.

The business has spent years getting the data and engineering foundations right. The platform is now in place, and the Head of Data is looking for a Data Scientist to help with turning that into models that improve real business decisions.

Think customer behaviour, risk, and operational efficiency. Real problems, real data, and models that make it into production.

What you'll be doing

  • Taking business problems from the initial question through to a deployed model
  • Building and validating models in Python, then monitoring performance once they're live
  • Using statistics, experimentation and A/B testing to properly test ideas
  • Working closely with Data Engineering on pipelines, features and productionisation
  • Going beyond dashboards when the problem needs something more sophisticated
  • Explaining the output clearly to senior stakeholders and keeping the focus on the business answer

What we're looking for

  • 2–3+ years' commercial Data Science experience
  • Strong statistical fundamentals across regression, classification, clustering, time series and experimental design
  • Strong Python, including pandas, NumPy and scikit-learn
  • Experience of taking models beyond the notebook and into production
  • Understanding of MLOps, CI/CD and model deployment, or experience working closely with engineers
  • A practical approach to modelling, with a preference for explainable solutions over unnecessary complexity

Nice to have

  • Financial services, fintech or another regulated environment
  • Microsoft Fabric, Azure ML or Databricks
  • MLflow, DVC and Git

The Why

You won't be joining a business that is still trying to work out what to do with its data.

The platform and engineering capability are already there. You'll have an established data team around you, a Head of Data who understands Data Science, and genuine scope to help to shape how modelling is used across the business.