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# Machine Learning Engineer / Data Scientist (SC Cleared)

- **Company:** Sanderson Recruitment Plc
- **Location:** London, UK
- **Salary:** £148,200.0
- **Contract:** Permanent contract
- **Skills:** Monitoring of Systems, Python (Programming Language), Live Connect (Windows), Machine Learning, Azure Machine Learning, SC Clearance, Databricks
- **Published:** August 4, 2026
- **Apply:** https://www.totaljobs.com/job/data-scientist/sanderson-government-and-defence-job107791035

## About the Role

* Active SC Clearance (must already be held).
 * Strong experience supporting production machine learning models running as live services.
 * Experience with:
 + Model monitoring
 + Drift detection
 + Retraining and model revalidation
 + Model governance and documentation
 * Strong Python skills and experience with standard machine learning tooling.
 * Ability to assess and support models built by other engineers or data scientists.
 * A pragmatic, risk-aware approach to production machine learning.

Desirable Experience

 * Azure Machine Learning.
 * Databricks.
 * Fairness, bias assessment, and model explainability.
 * Experience working in regulated or public sector environments.
 * Previous experience transitioning production models between suppliers.

About You

You're comfortable stepping into an existing environment rather than building everything from scratch. You understand the responsibility that comes with production models influencing operational decisions and know the importance of governance, transparency, and careful stewardship.

You recognise when a model is well managed-and when it isn't-and you're confident communicating what you can, and cannot, vouch for.

## Description

We're looking for an experienced Machine Learning Engineer / Data Scientist to take ownership of live supervised machine learning models already running in production within a government environment.

This is not a greenfield data science role. You'll be responsible for assessing, operating, and governing existing models that support operational decision-making. The focus is on understanding how models have been built, evaluating their monitoring and governance, and ensuring they can be safely transitioned from an incumbent supplier.

If you're comfortable inheriting someone else's work, asking the right questions, and making evidence-based judgements about what you can and cannot stand behind, we'd like to hear from you.

Key Responsibilities

 * Take ownership of supervised machine learning models currently in production.
 * Assess existing models, their performance, monitoring, and operational readiness.
 * Review model governance, documentation, and lifecycle processes.
 * Evaluate model drift, retraining strategies, and revalidation approaches.
 * Support the safe transition of production models from an existing supplier.
 * Provide clear technical assessments and recommendations for ongoing operation and governance.
 * Work closely with stakeholders to ensure models continue to meet operational and regulatory requirements.


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