Applied Data Scientist in AI & Geospatial Intelligence (KTP Associate)

This role will lead the technical development of a Rural Crime Information Platform, integrating social media intelligence, large language models (LLMs), geospatial analytics, and behavioural science to generate actionable insights for rural communities, insurers, and stakeholders. The postholder will design and implement end-to-end data pipelines, develop AI models to extract structured intelligence from unstructured social media data, build spatial risk models, and translate these outputs into a secure, user-facing web application. The role blends data engineering, applied AI, geostatistics and socio-behavioural modelling, supported by academic supervision and commercial mentoring.

This is a high-impact, technically ambitious role at the interface of research and product development. The role will require significant autonomy and responsibility, and the postholder will be expected to operate with a high degree of technical independence while being supported through structured training and governance.

Candidates should hold a postgraduate degree in a quantitative or computational field and have strong Python skills. Experience with AI or NLP methods, including LLMs cloud platforms, containerisation, APIs, relational databases and data pipelines is essential. Skills in geospatial analysis, GIS tools, frontend development or data visualisation are advantageous, as is familiarity with user centred or behavioural research. The role requires analytical strength, clear communication across disciplines, and the ability to tackle open ended technical challenges with independence and creativity.

Pre-employment screening: Due to Baseline Personnel Security Standard (BPSS) requirements, we can only consider applicants who hold existing Right to Work status in the UK. Proof of RTW will be required prior to any offer being confirmed.

The KTP Associate will work closely with farmers, insurers, and rural stakeholders to ensure the platform is grounded in real world needs and delivers meaningful value. By incorporating behavioural and criminological insights and leading participatory design activities, they will help shape a system that is practical, trusted, and easy to use. They will also maintain high quality documentation, contribute to academic and technical outputs, and support commercialisation and deployment activities as the platform moves from research into field testing and real-world application.