Defence Data Science & ML Lead (AI & Security)

Job description

Responsibilities

• Apply data science, machine learning and AI techniques creatively to solve complex problems.
• Research and develop innovative solutions that deliver real‑world impact.
• Pioneer implementation of new techniques and technologies.
• Participate in all phases of the lifecycle from capturing user needs and developing prototypes to scaling and managing live services.
• Be responsible for the high‑quality delivery of projects.
• Shape new propositions and support winning new projects.
• Support continual learning and development in the team.
• Develop deep understanding of the Defence and Security sector and the context for AI solutions and services to be successful.

Essential Skills and Experience

• Hands‑on experience of applying data science or machine learning in Defence/Security, wider public sector, or in academia.
• Understanding of a range of machine learning architectures and models (e.g. Transformers, CNNs, Generative AI) and understanding their applicability to client use cases.
• Strong communication skills, including preparing engaging and impactful reports and presentations and conveying complex issues to diverse audiences.
• Building productive relationships with colleagues and clients.
• Evidence of contribution to practice development, including developing new propositions, mentoring colleagues and supporting bid work.

Desirable Experience

• Experience applying state‑of‑the‑art techniques to derive insights from text, audio, imagery or video content.
• Experience with data‑science and machine‑learning services and toolkits from cloud providers (AWS, Azure, GCP) or equivalent.
• Practical experience with Python and good practice tools and processes for developing high‑quality code.
• Familiarity with common Python libraries for data management, statistical analysis, machine learning, visualisation, interactive web front‑ends.
• Experience with popular machine‑learning frameworks such as TensorFlow and PyTorch.
• Strong understanding of statistics and probability.
• Strong knowledge of the machine‑learning lifecycle, from prototyping state‑of‑the‑art to scaling and managing for enterprise use.
• Experience with one or more common workflow / pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents).
• Understanding of key considerations for Ethical and Responsible AI and experience applying them.

Requirements

• All applicants must hold UK security clearance to Developed Vetting level.
• Eligible based in London, Bristol or Manchester with hybrid working.

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