Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Geospatial Data Scientist

Syngenta
City of London
1 week ago
Create job alert
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 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 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.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer (UK)

R&D Senior Data Scientist

Senior Risk Modelling Data Scientist

Senior Risk Modelling Data Scientist

Senior Risk Modelling Data Scientist

Senior Risk Modelling Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.