Data Scientist

Datatech Analytics; Stanford Dingley; On-site; GBP 70,000 - 120,000; Full time

Job summary

Datatech Analytics is seeking a skilled ML engineer to build and deploy production-ready models. You will design end-to-end solutions, train models, and deploy them within a unified analytics platform.

You will collaborate with data engineering and analytics teams, monitor live model performance, and drive business impact by turning complex data into actionable insights for product, marketing, and finance.

Qualifications

• Proven experience building ML models in a commercial setting.
• Expert-level Python skills and strong statistical grounding.
• Experience with cloud or modern data environments (Azure/Databricks).

Responsibilities

• 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.
• Drive Business Impact: translate data into actionable predictions and partner with cross-functional teams.
• Ensure Model Excellence: monitor live performance, guard against data drift, champion MLOps best practices.

Skills

ML model development

Python programming

Data analysis

Communication

Tools

Pandas

NumPy

Scikit-learn

Azure

Databricks

Microsoft Fabric

Job description

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.

Requirements

• 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.