Data Scientist in Predictive Analytics KTP Associate

This 33-month fixed-term Knowledge Transfer Partnership (KTP) Associate position offers an exciting opportunity to join The Tomato Stall (trading as Isle of Wight Tomatoes) during a period of business growth and capability development. The successful candidate will lead the delivery of an innovative project focused on embedding advanced analytics and machine learning to integrate crop growth and sales forecasting into a single decision-support system, enabling agile and intelligent supply chain planning.

The Associate will work closely with both internal and external stakeholders to understand business requirements and ensure the developed solution aligns with strategic objectives. Responsibilities will include reviewing existing information systems and processes, designing a new decision-support infrastructure, and assessing current data capabilities to identify opportunities for improvement.

The role will involve collecting, cleaning and analysing data, experimenting with predictive analytics algorithms for both sales and crop growth forecasting, and implementing, refining and monitoring the resulting decision-support system. A key aspect of the position will be ensuring that new knowledge and capabilities are embedded within the business through staff training and stakeholder engagement throughout the project lifecycle.

As part of the KTP programme, the Associate will also contribute to knowledge dissemination activities, including attendance at two academic conferences and the production of two journal outputs. In addition, the post holder will support wider business activities as required, contributing to organisational goals beyond the core KTP project.

Isle of Wight Tomatoes aims to transform its forecasting and planning capability to reduce waste, optimise crop utilisation, and strengthen profitability in the UK fresh produce market. This Knowledge Transfer Partnership (KTP) will embed advanced analytics and machine learning to integrate crop growth and sales forecasting into a single decision-support system. Key objectives include developing predictive models for crop growth, using environmental and sensor data, forecasting demand based on weather, promotions, seasonal trends, and integrating these insights to enable dynamic planning across growing, sales and supply chain functions. The main areas of focus are algorithm development, IoT-enabled data capture, and ERP integration to ensure real-time connectivity and adoption. This KTP supports UK food security and sustainability by reducing carbon emissions and improving resource efficiency. It underpins strategic investment decisions, providing robust yield and demand projections to guide future glasshouse expansions and ensure payback expectations are met.