Senior Geospatial Data Scientist

Syngenta; Camden Town; On-site; GBP 45,000 - 60,000; Full time

Job summary

A leading agricultural solutions company based in Camden Town is seeking a Geospatial Data Scientist to leverage advanced geospatial analytics and machine learning to transform complex agricultural data into actionable insights. The ideal candidate will develop cutting-edge models and work collaboratively within cross-functional teams to address critical agricultural challenges. This role offers a dynamic environment focused on innovation in global food security and sustainable farming practices.

Qualifications

• Experience with advanced geospatial models and machine learning algorithms.
• Proficient in Python for geospatial data processing.
• Familiarity with satellite imagery and IoT sensor data.

Responsibilities

• Develop and implement advanced geospatial models.
• Design and maintain scalable data processing pipelines.
• Lead statistical analysis to identify patterns in agricultural data.
• Deliver well-documented code for geospatial data processing.
• Translate geospatial insights into practical agricultural recommendations.

Skills

Geospatial analytics

Machine learning

Remote sensing

Data processing

Python

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 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.