Senior Geospatial Data Scientist

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

Descripción de la vacante

A leading agricultural technology company is looking for a Geospatial Data Scientist to transform agricultural and earth observation data into insights. The candidate will use advanced geospatial analytics and machine learning to tackle critical challenges in agriculture, focusing on innovation to improve food security. The role demands a strong background in geospatial analysis, Python programming, and collaboration with various teams.

Servicios

Generous benefits package

Flexible working arrangements

Learning culture with a wide range of training options

Formación

• Minimum of 5 years experience in satellite and geospatial data analysis.
• Strong proficiency in Python with experience in geospatial libraries.
• Experience with cloud-based geospatial processing.

Responsabilidades

• Develop and implement advanced geospatial models.
• Design scalable data processing pipelines.
• Deliver high-quality code for geospatial data processing.

Conocimientos

Python programming

Geospatial analysis

Machine learning

Statistical analysis

Communication skills

Educación

Masters or PhD in Geographic Information Science, Remote Sensing, Computer Science, or related field

Herramientas

GeoPandas

Rasterio

Google Earth Engine

Spark

Git

Descripción del empleo

The Geospatial Data Scientist will 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 extract meaningful patterns from diverse spatial datasets, enabling data‑informed agricultural decision‑making that supports 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 solutions that address critical challenges in modern agriculture through the power of spatial data science.

Accountabilities

• Develop and implement advanced geospatial models and machine learning algorithms to extract actionable insights from agricultural datasets, including satellite imagery, drone data, and IoT sensors.
• Design and maintain scalable data processing pipelines for cleaning, transforming, and integrating diverse geospatial data sources.
• Lead statistical analysis and data mining initiatives to identify meaningful patterns and relationships in spatial and temporal agricultural data.
• Deliver high-quality, well-documented code for geospatial data processing using Python and relevant libraries.
• Translate complex geospatial insights into practical recommendations for agricultural management and decision‑making.
• Pioneer innovative approaches for feature extraction from remote sensing data to enhance model performance.
• Implement cloud‑based solutions for large‑scale geospatial data processing and analysis.
• Maintain technical leadership by staying current with advancements in geospatial technologies and machine learning techniques.
• Contribute to technical reports, scientific publications, and presentations to communicate research findings.
• Collaborate effectively with interdisciplinary teams, including agronomists, data scientists, and software engineers.

Qualifications

• Masters or PhD in Geographic Information Science, Remote Sensing, Computer Science, Data Science, or a related field with a strong focus on geospatial analysis.
• Minimum of 5 years of experience in satellite and geospatial data analysis and modelling, preferably in an agricultural or environmental context.
• Strong proficiency in Python programming with experience in geospatial libraries such as GeoPandas and Rasterio.
• Expertise in machine learning and deep learning techniques, particularly as applied to earth observation problems (e.g. image classification, object detection, time‑series analysis).
• Experience with cloud‑based geospatial processing and big‑data technologies (e.g. Google Earth Engine, Spark).
• Experience leveraging 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 routine 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 communicate complex technical concepts to non‑technical audiences.
• Familiarity with agronomy concepts and agricultural systems is a plus.

Additional Information

Location: Remote working is possible within Spain.

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, and life insurance.
• Flexible working arrangements.
• We offer a position that contributes to valuable and impactful work in a stimulating and international environment.
• Learning culture ("Together we Grow") and a 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.

Remote Work: Yes

Employment Type: Full‑time