Senior Geospatial Data Scientist

Syngenta Seeds; City Of London; Remote; GBP 50,000 - 70,000; Full time

Job summary

A global agricultural technology leader is seeking a Geospatial Data Scientist to transform agricultural data into actionable insights. This remote role involves developing innovative models and collaborating with cross-functional teams to enhance sustainable farming practices. Ideal candidates will possess a Master's degree, extensive experience in geospatial data analysis, and strong Python programming skills. The company offers a comprehensive benefits package and flexible working arrangements.

Benefits

Generous pension scheme

Bonus scheme

Private medical & life insurance

Flexible working arrangements

Qualifications

• 5+ years of experience in satellite and geospatial data analysis.
• Proficiency in Python with experience in geospatial libraries.
• Expertise in machine learning for earth observation applications.

Responsibilities

• Develop and implement geospatial and machine learning models.
• Design large data pipelines for integrating geospatial data.
• Perform statistical analysis to inform agricultural management strategies.
• Engineer features from remote sensing data to enhance model accuracy.

Skills

Geospatial data analysis

Machine learning

Python programming

Data visualization

Remote sensing expertise

Education

Master’s degree in Geographic Information Science

Tools

GeoPandas

Rasterio

Google Earth Engine

Spark

Job description

Company Description

Syngenta Group, a global leader in agricultural technology and innovation, employs 60,000 people across more than 100 countries to transform agriculture through tailor‑made solutions for farmers, society, and our planet. Our diverse portfolio encompasses seeds, crop protection, nutrition products, agronomic solutions, and digital services, all designed to help farmers produce healthy food, feed, fiber, and fuel while conserving natural resources and protecting the environment. Our mission is to address critical challenges such as climate change and food security through sustainable practices and cutting‑edge solutions, while safeguarding the planet’s resources.

Job Description

The Geospatial Data Scientistwill leverage advanced geospatial analytics, machine learning, and remote sensing expertise to transform complex agricultural and earth observation data into actionable insights that drive innovation in Syngenta’s Computational Agronomy Department. This role will develop cutting‑edge models and algorithms that enable data‑informed agricultural decision‑making, supporting Syngenta’s mission to improve global food security and sustainable farming practices.

Working within cross‑functional teams, the Geospatial Data Scientist will bridge technical expertise with agricultural knowledge to create scalable, data‑driven solutions for modern agricultural challenges.

Accountabilities

• Develop and implement advanced geospatial and machine learning models to analyze agricultural datasets (satellite imagery, drone data, IoT sensors) and extract meaningful patterns.
• Design, build, and maintain scalable, cloud‑enabled large data pipelines for cleaning, transforming, and integrating diverse geospatial data sources.
• Perform statistical analysis and data mining to uncover spatial and temporal trends that inform agricultural management strategies.
• Engineer innovative features from remote sensing data to enhance model accuracy and performance.
• Deliver high‑quality, documented code for geospatial data processing using Python and relevant libraries.
• Translate analytical results into practical recommendations for agronomists, growers, and decision‑makers.
• Stay current with advancements in geospatial technologies, remote sensing, and machine learning to maintain technical leadership.
• Contribute to technical reports, scientific publications, and presentations to share research outcomes.
• Collaborate closely with interdisciplinary teams, including agronomists, data scientists, and software engineers.

Qualifications

Critical Knowledge & Experience

• Master’s degree in Geographic Information Science, Remote Sensing, Computer Science, Data Science, or a related field with a strong focus on geospatial analysis.
• 5+ years of experience in satellite and geospatial data analysis and modeling.
• Proficiency in Python programming, with experience in geospatial libraries such as GeoPandas, Rasterio, and related tools.
• Expertise in machine learning for earth observation applications (e.g., image classification, object detection, time series analysis).
• Experience with geospatial foundation models.
• Experience with version control systems (e.g., Git) and collaborative software development practices.
• Experience leveraging generative AI tools to optimize workflows, automate tasks, and enhance productivity in geospatial analysis and data science projects.

Skills

• Excellent written and verbal communication skills in English.
• Strong analytical and problem‑solving skills, with the ability to explain complex technical concepts to non‑technical audiences.

Nice to have

• PhD in a relevant field.
• Familiarity with agronomy concepts and agricultural systems.
• Expertise in deep learning techniques.
• Experience with cloud‑based geospatial processing and big data technologies (e.g., Google Earth Engine, Spark).

Additional Information

Location: Remote working is possible within UK.

Portfolio submission: Please provide examples of relevant geospatial data science projects.

What we offer?

• Extensive benefits package including a generous pension scheme, bonus scheme, private medical & life insurance.
• Flexible working arrangements.
• We offer a position which contributes to valuable and impactful work in a stimulating and international environment.
• Learning culture (Together we Grow) and wide range of training options.

Equal Opportunity

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.