Computational Agronomy Scientist

Syngenta Group; A distancia; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A leading agricultural innovator is seeking a Computational Agronomy Scientist based in Spain. The role involves developing intelligent recommendation systems and decision support models to optimize the use of agricultural products. Candidates should have a strong agronomic background and proficiency in Python for data analysis, with at least 5 years of relevant experience. This position encourages collaboration with diverse teams to enhance crop management and improve plant health globally. Remote work is available, fostering work-life balance and professional growth.

Servicios

Comprehensive benefits package

Generous annual leave

Wellness programs

Learning and development opportunities

Formación

• MS degree in Agronomy or a related agricultural sciences field is essential.
• 5 years of experience in building predictive models or agricultural data analysis is required.
• Proficiency in English for international collaboration is a must.
• Strong Python skills with experience in data analysis libraries are necessary.
• Understanding of statistics and AI/ML techniques is critical.
• Knowledge of crop production systems and pest management is essential.

Responsabilidades

• Develop agronomic models and data-driven recommendation systems.
• Build and validate predictive models for Crop Protection.
• Analyze diverse agricultural datasets for actionable insights.
• Design field experiments and interpret trial results.
• Create data processing pipelines using Python.

Conocimientos

Python programming

Data analysis

Predictive modeling

Machine learning

Analytical skills

Educación

MS degree in Agronomy or related field

PhD in Agronomy or related field

Herramientas

Pandas

NumPy

Scikit‑learn

Matplotlib

Seaborn

Plotly

Descripción del empleo

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 Syngenta's 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.

Responsibilities

• 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 datasets—including R&D field trials, on‑farm demonstrations, weather data, soil characteristics, pest monitoring, and agronomic scouting records—to 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.

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 the 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

Remote Work: Yes

Employment Type: Full‑time

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.

Key Skills

• Laboratory Experience
• Immunoassays
• Machine Learning
• Biochemistry
• Assays
• Research Experience
• Spectroscopy
• Research & Development
• cGMP
• Cell Culture
• Molecular Biology
• Data Analysis Skills

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.

EEO Statement

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.