About this role
Developing algorithms and machine learning models that extract insights from satellite imagery time series forms the core daily activity for the data scientist joining Planet. Operating within a hybrid framework from the Haarlem office, the engineering group builds validated markers and cloud-based platforms that process dense temporal stacks of satellite data for agricultural and environmental monitoring across Europe. Engineers take research topics from initial exploration through production deployment while managing the codebase collaboratively.
Candidates comfortable working with AI agents, satellite imagery, and spatial datasets will find alignment with the team's technical scope. The position requires end-to-end ownership of marker results for production deliveries, along with documentation and cross-functional communication through research reports and blog posts.
What you will do
- Develop algorithms and machine learning models to extract insights from satellite imagery time series.
- Take research topics from initial exploration through to production deployment.
- Own marker results for production Area Monitoring System deliveries across several European countries by reviewing quality before client delivery.
- Explore and build embeddings-based insight extraction in areas beyond the Common Agricultural Policy.
- Incorporate AI agents into daily workflows and assist the team in adopting similar tools.
- Co-own the markers codebase collaboratively with other team members.
- Document and organize work to ensure transparency and repeatability through internal research reports and public posts.
What you need
- Have at least four years of relevant professional experience in a technical domain.
- Hold a bachelor's degree or higher in computer science, data science, or another STEM field.
- Demonstrate an understanding of machine learning principles including model validation and performance evaluation techniques.
- Show proficiency in Python programming with the ability to write maintainable and well-documented code.
- Bring experience working with AI agents and modern machine learning tools.
- Maintain familiarity with version control, Git, and shared codebases.
- Possess a working knowledge of the geospatial domain and professional proficiency in English.
Nice to have
- Experience working with embeddings or other learned representations of imagery
- Remote sensing expertise, particularly with satellite time series
- Experience processing radar data such as Sentinel-1
- Familiarity with the agricultural domain or the EU Common Agricultural Policy
- Experience with cloud environments and distributed computing
Benefits
- Paid time off including vacation, holidays and company-wide days off
- Employee Wellness Program
- Home Office Reimbursement
- Monthly Phone and Internet Reimbursement
- Tuition Reimbursement and access to LinkedIn Learning
- Equity
Skills and tech stack
Questions candidates ask
What is the remote work and office policy for this role?
This is a full-time, hybrid role which will require you to work from our Graz, Ljubljana or Haarlem office 3 days per week.
What is the expected compensation for the position?
The expected starting gross salary range for this role in the Netherlands is €59.200 — €74.000 EUR, with individual placement determined objectively based on skills, qualifications, and professional experience.
What kind of data and technical tools will I be working with?
You will work with multi-sensor Earth observation data, satellite imagery time series, Python programming, Git version control, and AI agents.
How are applications reviewed and processed?
Applications are reviewed on a rolling basis, and the posting may be removed earlier than projected if a suitable pool of applications has been received.