SC Cleared Data Scientist – Contract
Rate: Up to £650 per day (Inside IR35)
Location: London or Manchester (1-2 days per week on‑site)
Contract: 6 months
Clearance: Active SC required
We're hiring an experienced SC‑cleared Data Scientist to support a high‑profile central government programme delivering advanced analytics and machine‑learning solutions. This role focuses on turning complex datasets into predictive insight and deployable models that directly inform policy and operational decision‑making.
You will work within a multidisciplinary data team, partnering with data engineers, architects, and analysts to design, build, and productionise machine‑learning models using modern Python and MLOps practices across secure cloud environments.
Key Requirements
* Active Security Clearance (SC) – must be current and transferable
* Proven experience as a Data Scientist in central government or regulated environments
* Strong hands‑on experience with Python for data science and machine learning
* Solid understanding of machine‑learning techniques (supervised, unsupervised, model evaluation)
* Experience with MLOps practices, including:
o Model versioning and deployment
o CI/CD for ML workflows
o Monitoring and performance management
* Experience working with cloud‑based data platforms (AWS and/or Azure)
* Strong statistical knowledge and ability to explain complex models to non‑technical stakeholders
Responsibilities
* Design, build, and evaluate machine‑learning models to solve real‑world government problems
* Use Python and related libraries to explore, transform, and model complex datasets
* Work with engineers to integrate models into production pipelines using MLOps best practices
* Validate, test, and monitor models to ensure accuracy, reliability, and fairness
* Collaborate closely with analysts and policy teams to translate analytical findings into insight
* Ensure solutions meet security, governance, and ethical standards
* Clearly communicate findings and recommendations to senior stakeholders
Working Pattern
* 1-2 days per week on‑site in London or Manchester
* Remaining days remote, offering a flexible hybrid working model
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