At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. The Research Data Associate is responsible for managing, analyzing, and optimizing research and trialing data to support Syngenta鈥檚 trialing and product placement activities across Europe. This role ensures data accuracy, develops automated reporting solutions, and drives innovation in digital tools and analytical workflows. The successful candidate will work closely with trialing, product placement, and data scientists to deliver actionable insights, improve operational efficiency, and enable data-driven decision-making.
Key Responsibilities
1. Data & Database Management
- Maintain high-quality research and trialing databases.
- Use SQL to retrieve, combine, and transform data from multiple sources.
- Connect diverse databases to support analytical projects.
- Automate data processes to reduce manual work, duplication, and errors.
2. Reporting & Analytics
- Analyze trialing and research data with product placement and agronomy experts.
- Develop and maintain automated dashboards and reports combining multiple data sources.
- Support assessment of commercial performance, genetic progress, registration status, and budget tracking.
- Translate complex data into clear, actionable insights.
3. Experiment & Trial Support
- Act as a key expert for experiment creation, material management, and experimental design.
- Support GIS analysis, spatial visualization, and data interpretation.
- Ensure experiments follow statistical and agronomic best practices.
- Serve as a regional contact for digital research tools and liaise with software development teams.
4. Data Collection & Processing
- Support and pilot advanced phenotyping solutions (robots, drones, sensors).
- Analyze and interpret phenotypic data (e.g. plant populations, herbicide injury, stress indicators).
- Contribute to protocols and scalable, automated data collection workflows.
- Support adoption of data science, big data, and AI-based approaches in agricultural research.
5. Digital Tools & Innovation
- Act as regional tools expert and trainer for product placement and trialing teams.
- Test, validate, and implement new digital tools (e.g., SAP thresholds, phenotyping fleet management).
- Propose improvements to experimental designs and workflows.
- Manage phenotyping equipment and coordinate drone data acquisition.
- Support adoption of machine learning and AI-based analysis.