Data Scientist

Please Note, youmust onlyhold a British passport, and youmusthold DV Clearance with the MoD (not DWP, Home Office etc)

As a Data Scientist, you will:

• Design, develop, and test solutions to collect, integrate, and prepare data for advanced analytics and machine learning applications.
• Analyse complex datasets to uncover trends, patterns, and actionable insights that drive business or operational outcomes.
• Build, prototype, and evaluate statistical and machine learning models to solve real-world problems, testing feasibility and estimating impact before full deployment.
• Engineer and implement ML-based solutions, owning the full lifecycle – from model development and deployment to monitoring and iteration.
• Deploy models into production environments, handling the integration and operationalisation of ML within wider systems and applications.
• Continuously evaluate and monitor model performance, identifying degradation, performance gaps, or opportunities for optimisation.
• Collaborate closely with data analysts, engineers, and other stakeholders to define new tools, enhance workflows, and support innovation across teams.
• Communicate findings, recommendations, and model outcomes to both technical and non-technical audiences through visualisation and data storytelling.
• Research emerging AI/ML techniques to stay ahead of the curve and identify new opportunities to enhance current systems.
• Ensure all data science and ML practices adhere to relevant ethical standards, policies, and governance frameworks.
• Provide technical guidance and mentorship on ML implementation across cross-functional teams.

About You

• You have a strong foundation in data science, analytics, or machine learning, with hands-on experience developing models that solve practical problems and deliver measurable impact.
• You are comfortable working across the full machine learning lifecycle – from exploratory data analysis and model prototyping to production deployment, integration, and ongoing monitoring.
• You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings.
• You have deployed models into live systems and understand how to make ML operational – whether that means working with APIs, integrating into existing applications, or using containerisation tools like Docker.
• You actively monitor the performance of deployed models, and are experienced in identifying drift, re-training triggers, or opportunities for optimisation.

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