Job Description
Planet designs, builds, and operates the largest constellation of imaging satellites in history.
Key Responsibilities
- 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 Ljubljana office 3 days per week.
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 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-solving skills in technical or analytical domains.
- Professional working proficiency in English, the language of the company.
- Experience working with embeddings or other learned representations of imagery.
- Remote sensing expertise, particularly with satellite time series.
- Experience processing radar data (for example Sentinel-1).
- Familiarity with the agricultural domain, or with the EU Common Agricultural Policy and area-based payment schemes.
- Experience with cloud environments and distributed computing.
Benefits & Perks
- These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.
- 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
- Volunteering Paid Time Off
Ready to Apply?
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