The UK Agri-Tech Centre
Data Modeller
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Data Modeller
Department: Finance & Operations Employment Type: Full Time Location: Any hub Compensation: £45,000 - £55,000 / year
Description
Strategy and Values
The Agri-Tech Centre’s mission is to accelerate the adoption of technology across UK agriculture and food production. We connect the people and organisations needed to turn promising ideas into solutions that work in the real world. As a trusted, independent national organisation with strong regional relationships, we turn insight into action, help the sector act on shared priorities and support a more productive, profitable, resilient and sustainable agri-food economy for the UK.
Everything we do is underpinned by our organisational values: we do the right thing with integrity, accountability and respect for others; we inspire and innovate through curiosity and proactive thinking; we make a difference by focusing on meaningful future impact; and we build and connect through collaboration, trust and strong relationships.
Job Purpose
The Data Modeller develops robust, evidence-led models that translate complex agricultural, environmental, economic and technology data into actionable insight. Working within the Data & Intelligence team, the role will develop and apply quantitative modelling approaches to understand technology performance, sustainability, resilience, adoption, economic viability and system-level impacts across UK agriculture and food production. The role will support both the Agri-Tech Centre's core funded activities and the development of commercial Data & Intelligence services, creating reusable modelling approaches that enable customers, partners and internal teams to explore scenarios, understand uncertainty, compare interventions and make better-informed decisions.
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Key Responsibilities
- Develop quantitative models to assess agricultural technologies, interventions and production systems across environmental, economic, operational and wider system impacts.
- Apply methods such as Life Cycle Assessment (LCA), Techno-Economic Assessment (TEA), system dynamics, scenario, uncertainty and adoption modelling.
- Create reusable frameworks, baselines and decision-support tools by integrating structured, geospatial, environmental and economic evidence.
- Work with customers and partners to define analytical needs and communicate clear insights, assumptions, uncertainties and limitations.
- Support the development of commercially valuable Data & Intelligence services by applying modelling capability to industry challenges.
- Deliver reproducible, well-governed analysis across multidisciplinary projects, with appropriate documentation, data-quality assessment and peer review.
Skills, Knowledge and Expertise
Essential
- Degree or equivalent experience in a relevant quantitative, agricultural, environmental, economic, engineering or scientific discipline.
- Experience developing quantitative models for analysis and decision-making, using approaches such as LCA, TEA, system dynamics, economic, scenario or adoption modelling.
- Strong analytical skills, including the ability to work with complex, incomplete and varied evidence.
- Strong stakeholder and collaborative skills, with the ability to translate customer needs into analytical requirements.
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Desirable
- Experience applying modelling in agriculture, food, agri-tech, sustainability or a related sector.
- Knowledge of LCA standards and sustainability assessment, simulation, sensitivity or uncertainty methods.
- Experience creating reusable modelling frameworks, baseline datasets or decision-support tools that integrate environmental, economic, operational or geospatial evidence.
- Experience in commercial, consultancy, funding or customer-facing analytical projects, using relevant modelling, statistical, visualisation or programming tools.
Additional Information
This multidisciplinary, customer-facing role requires flexibility across agricultural sectors, technologies and analytical challenges. The postholder will select methods to suit the decision need, communicate complex analysis clearly to internal and external stakeholders, and adapt as the Agri-Tech Centre’s Data & Intelligence services develop.
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