Computational Agronomy Scientist

At Syngenta we are building a collaborative team dedicated to advancing agriculture through science and innovation. Our Computational Agronomy Science team is seeking a Computational Agronomy Scientist based in Spain to develop intelligent recommendation systems and decision support models that optimize the use of Syngentas Seed and Crop Protection products.

In this role you will bridge agronomic expertise with data science to create digital solutions that directly support farmers worldwide. Working with interdisciplinary teams including agronomists data scientists engineers and product managers you will translate complex agricultural challenges into practical data-driven solutions that enhance crop management and protect plant health.

• Develop and implement agronomic models and data-driven recommendation systems for plant health protection and crop management optimization including product selection and timing planting decisions fertilization irrigation and harvest timing.
• Design build and validate predictive models supporting our Crop Protection portfolio (fungicides insecticides herbicides seed treatments and biologicals).
• Analyze and integrate diverse agricultural datasetsincluding R&D field trials on-farm demonstrations weather data soil characteristics pest monitoring and agronomic scouting recordsto generate actionable insights.
• Design and analyze field experiments including statistical validation data quality assessment and interpretation of multi-location trial results to support product development and agronomic recommendations.
• Create data processing pipelines using Python to clean transform and analyze agricultural datasets for model development and validation.
• Develop presentations and visualizations to communicate model outcomes and analytical findings to both technical and non-technical stakeholders.

Qualifications :

Required Qualifications: 

• MS degree in Agronomy or related agricultural sciences (PhD preferred).
• 5 years of professional experience building predictive models or in roles involving agricultural data analysis.
• Proficient English language skills (written and verbal) for international team collaboration.
• Strong proficiency in Python programming with experience in data analysis libraries (e.g. Pandas NumPy Scikit-learn) and visualization tools (e.g. Matplotlib Seaborn Plotly)
• Understanding of applied statistics and experience applying AI/ML techniques including supervised learning time series forecasting clustering segmentation and Bayesian inference.
• Comprehensive knowledge of crop production systems including agronomic management practices growth stages yield-limiting factors and crop protection practices.
• Strong understanding of pest management (insects diseases weeds) including pest lifecycles economic thresholds ROI concepts and integrated pest management (IPM) principles.
• Practical knowledge of field-level agronomic research protocols including plot management data recording and quality control in experimental settings.
• Demonstrated ability to leverage generative AI tools (ChatGPT Claude GitHub Copilot) to enhance productivity and accelerate problem-solving.

Professional Capabilities:

• Strong analytical and problem-solving skills with ability to bridge agronomic knowledge and computational methodologies.
• Ability to work independently and collaboratively in a fast-paced innovation-driven environment while focusing on key priorities.
• Ability to translate technical solutions into practical business outcomes with clear value for customers.

Desired Qualifications:

• Professional experience in agricultural research crop consulting digital agronomy or related agricultural data analysis roles.
• Experience with machine learning frameworks such as CatBoost XGBoost LightGBM PyMC and StatsModels.
• Experience with crop simulation models (DSSAT or APSIM).
• Experience working with geospatial datasets.
• Experience in cloud environments such as Amazon SageMaker.
• Experience collaborating with data engineers and ML engineers to develop optimize and deploy model solutions.
• Familiarity with Agile software development principles and tools.
• Knowledge of agrometeorology and its application to pest forecasting.
• Familiarity with field monitoring using IoT devices sensors soil and plant sampling and scouting techniques.

Additional Information :

What We Offer:
An environment where every voice matters professional growth is encouraged and work-life balance is prioritized.
Comprehensive benefits package that starts from day one including health and wellness coverage tailored to your location.
Generous annual leave entitlement learning and development opportunities wellness programs employee assistance programs and additional benefits in accordance with local practices.

Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment hiring training promotion or any other employment practices for reasons of race color religion gender national origin age sexual orientation marital or veteran status disability or any other legally protected status. 

#LI-Remote

Remote Work :

Yes

Employment Type :

Full-time