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Salary: EUR 54,100 - 67,600 / annual
Planet designs, builds, and operates the largest constellation of imaging satellites in history, delivering empirical Earth observation data via a cloud-based platform to commercial, environmental, and humanitarian sectors. We are seeking a Data Scientist to join our team in Graz (with flexibility to work from Ljubljana or Haarlem offices) to develop high-quality, validated markers that extract insights from dense temporal stacks of satellite imagery across agriculture, land management, and climate.
In this role, you will own the development of algorithms and machine learning models that extract insights from satellite imagery time series, maintaining and improving existing markers. You will take research topics from exploration through to production, owning marker results for production Area Monitoring System (AMS) deliveries across several EU countries—running them, reviewing them, and confirming quality before they reach clients. You will explore and build embeddings-based insight extraction in new areas beyond the Common Agricultural Policy (CAP), use AI agents in your daily work, and help the team improve their application. You will co-own the markers codebase with the rest of the team, collaborate to iteratively build solutions on the platform, and document your work to ensure transparency and repeatability. Additionally, you will write internal research reports, public blog posts, and reports for clients.
This is a full-time hybrid role requiring 3 days per week in office. You will work with multi-sensor Earth observation data to solve complex environmental and agricultural challenges, collaborating closely with scientists and engineers to deploy models at scale.
REQUIREMENTS:
- 4+ years of relevant work experience
- Bachelor's degree or higher in computer science, data science, or another STEM field
- Understanding of machine learning principles, including model validation and performance evaluation techniques
- Proficiency in Python programming with ability to write maintainable, well-documented code
- Experience working with AI agents and modern machine learning tools
- Experience with version control and Git, and comfort working in a shared codebase
- Working knowledge of the geospatial domain
- Ability to deliver projects on schedule and manage technical deliverables
- Problem-solving skills in technical or analytical domains
- Professional working proficiency in English
DESIRABLE:
- Experience working with embeddings or other learned representations of imagery
- Remote sensing expertise, particularly with satellite time series
- Experience processing radar data (e.g., Sentinel-1)
- Familiarity with the agricultural domain or EU Common Agricultural Policy and area-based payment schemes
- Experience with cloud environments and distributed computing
