Develop and validate machine-learning and predictive models for Crop Protection R&D using complex scientific, laboratory, environmental, and field-trial data. Collaborate with multidisciplinary scientists and software teams, guide experimental design, support data strategy, communicate insights to technical and non-technical stakeholders, track modelling impact, document methods, and mentor junior data professionals.

Develop predictive and statistical models for Crop Protection R&D using experimental and heterogeneous datasets. Collaborate with scientific experts, support experimental design and field trials, and prototype GenAI applications including RAG, knowledge extraction, knowledge graphs, and agentic workflows. Evaluate and govern AI tools, contribute to responsible AI and data governance practices, and work with engineering teams to deploy analytical solutions.