Data Scientist
Listed on 2026-09-30
-
Software Development
Data Scientist, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Welcome to Planet. We believe in using space to help life on Earth.
Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud‑based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one.
Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world's toughest obstacles.
As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains.
We have a people‑centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world.
Planet is a global company with employees working remotely world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands.
About the Role:We are looking for a Data Scientist to join our team in developing high‑quality, validated markers that extract insights from dense temporal stacks of satellite imagery across agriculture, land management, and climate. The markers you build form the core of our Area Monitoring System (AMS) delivered to Common Agricultural Policy paying agencies across Europe, owned end‑to‑end from method to production code.
You will collaborate closely with scientists and engineers to deploy models at scale, while expanding beyond compliance into land‑cover change detection using embeddings and AI‑first workflows.
Ideal candidates are adaptable, curious about AI agents, and eager to iterate directly based on customer feedback. As a member of this team, you will have the opportunity to work with multi‑sensor Earth observation data to solve complex environmental and agricultural challenges.
This is a full‑time, hybrid role which will require you to work from our Graz, Ljubljana or Haarlem office 3 days per week.
Impact You'll Own:- Develop algorithms and machine learning models that extract insights from satellite imagery time series, and maintain and improve the markers we already run.
- Take a research topic from exploration through to production.
- Own marker results for production AMS deliveries across several EU countries - run them, review them, and confirm quality before they reach the client.
- Explore and build embeddings‑based insight extraction in new areas beyond CAP.
- Use AI agents in your daily work, and help the team get better at it.
- Co‑own the markers codebase together with the rest of the team.
- Collaborate with the team to iteratively build solutions on our platform and existing data building blocks, and inspire and enable our partners to extract insights using them.
- Document and organize your work to be transparent and repeatable.
- Write internal research reports, public blog posts, and reports for clients.
- 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 the 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‑solvi…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).