Senior Geospatial Data Scientist at Syngenta Group

Madrid, Community of Madrid, Spain -

Full Time

Start Date

Immediate

Expiry Date

01 Feb, 26

Salary

0.0

Posted On

03 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Geospatial Analytics, Machine Learning, Remote Sensing, Python Programming, Data Processing, Statistical Analysis, Data Mining, Feature Extraction, Cloud-Based Solutions, Geospatial Data Analysis, Collaboration, Agronomy Knowledge, Generative AI, Big Data Technologies, Version Control, Documentation

Industry

Farming

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 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 Critical Knowledge & Experience Master's 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 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 & 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.

Responsibilities

The Geospatial Data Scientist will develop advanced geospatial models and machine learning algorithms to extract actionable insights from agricultural datasets. This role involves collaborating with cross-functional teams to create scalable solutions that address challenges in modern agriculture.