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# Data Scientist

- **Company:** Datatech Analytics
- **Location:** Berkshire, UK
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Microsoft Azure, Information Engineering, Data Infrastructure, Python (Programming Language), Machine Learning, NumPy, Transaction Data, Pandas, Microsoft Fabric, Scikit Learn, Data Analytics, Data Management, Machine Learning Operations, Databricks
- **Published:** September 18, 2026
- **Apply:** https://www.careerjet.co.uk/job/gb5a5a3175a79007ee4e029b745abd9903/eaa

## About the Role

·Proven experience building and iterating on ML models in a commercial setting.
·Expert-level Python skills (pandas, NumPy, scikit-learn, etc.) and strong statistical grounding.
·Experience working within cloud or modern data environments (Microsoft Fabric, Azure, or Databricks).
·Clear, impactful communication skills to bridge technical models and business outcomes.
This is an exceptional opportunity for a candidate who wishes to help shape DS within an established business that has embraced new data platforms through smart business decisions and a collaborative data function.

## Description

Are you ready to shape the future of predictive analytics in financial services? We are looking for a versatile Data Scientist to help to build and scale our clients data science practice. Sitting at the heart of the Data team, you will apply machine learning, predictive modelling, and statistical rigor to tackle real world business challenges across customer behaviour, risk, and pricing.
What You'll Do
·Build End-to-End Solutions: Scope, design, train, and deploy production-ready ML models and statistical experiments.
·Shape the Platform: Collaborate with Data Engineering and Analytics to build reproducible pipelines and integrate workloads into a Unified, AI-powered analytics platform.
·Drive Business Impact: Translate raw, complex transactional data into actionable predictions and partner with cross-functional teams (Product, Marketing, Finance) to unlock competitive advantage.
·Ensure Model Excellence: Monitor live model performance, guard against data drift, and champion best practices in MLOps.


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