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Data Scientist - Agriculture

Job in Bracknell, Berkshire, SL5 8RU, England, UK
Listing for: Syngenta
Full Time position
Listed on 2026-01-10
Job specializations:
  • Research/Development
  • Science
Job Description & How to Apply Below

Company Description

Syngenta Crop Protection is a leader in agricultural innovation, bringing breakthrough technologies and solutions that enable farmers to grow productively and sustainably. We offer a leading portfolio of crop protection solutions for plant and soil health, as well as digital solutions that transform the decision‑making capabilities of farmers. Our 17,900 employees serve to advance agriculture in more than 90 countries around the world.

Syngenta Crop Protection is headquartered in Basel, Switzerland, and is part of the Syngenta Group.

Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture!

Job Description

Position:
Data Scientist - Agriculture

Location: We could consider candidates based at additional locations within Europe

Application process: Carefully read instructions in "Additional Information" section

We have an exciting opportunity for Data Scientists to join our Global Data Analytics & Predictive Science Team in Product Biology department. Within these roles you will work on Syngenta historical biological data to uncover patterns and deliver new data‑driven insights for active ingredient development across R&D functions. You will be asked to analyse and interpret the outcome of scientific experiments with your analytical skills as well as machine learning approaches.

Your work will bring forward our understanding of biological performance in crop protection and guide design, optimization and development of novel crop protection solutions. Key responsibilities will include:

  • Driving historical data analysis of biological field trials by identifying patterns and analyzing the impact of key factors including product formulations, rates, mixtures, agricultural practices, and environmental conditions on product performance.
  • Supporting domain experts in understanding product performance and identifying analytics opportunities to drive business value.
  • Contributing to strategic business initiatives across Crop Protection R&D by interpreting physical chemistry, biokinetic, formulation, marketing and environmental data to support decision taking and design laboratory, glasshouse and field trials.
  • Guiding technical managers in designing field trials aimed at validating scientific hypotheses and model predictions.
  • Working with R&D IT and software developers to improve data‑models integrations and to deploy applications tailored on shareholders’ needs.
  • Monitoring and exploring new modelling approaches, analytical tools and methodologies.
  • Engaging with high‑priority digital transformation projects to understand opportunities to accelerate the impact of data science for predictive field trialing.
  • Working with colleagues and external collaborators understanding their complementary capabilities and integrating them into projects and initiatives.
Qualifications

What we are looking for

  • Strong foundations in data science at postgraduate level with applications in natural sciences (e.g. biology, ecology, environmental sciences).
  • Proven experience in the use of the main data‑science, analytics, modelling and visualization Python libraries, including machine learning and deep learning ones.
  • Scientific domain knowledge in related fields such as environmental sciences or biology.
  • Prior experience in developing machine‑learning models relevant to biological or crop protection outcomes.
  • Hands‑on experience leveraging generative AI (genAI) approaches for data exploration, model development, or research acceleration is a plus.
  • Knowledge of data analysis and extracting data insights and new understanding, while communicating scientific and data concepts to specialist and non‑specialist audiences.
  • Adaptability to different business challenges and data types / sources and to learn and utilize a range of different analytical tools and methodologies.
  • Ability to visualize and story‑telling with data to communicate results to shareholders with different levels of technical proficiency.
  • Analytical…
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