Satellite Imagery Data Scientist | AI & Time-Series

Planetlabs; Haarlem; Hybrid; EUR 59,000 - 74,000; Full time

Benefits offered by this job

Paid time off

Wellness program

Home office reimbursement

Phone & internet reimbursement

Tuition reimbursement

Equity

Volunteering PTO

Job summary

Planet is seeking a Data Scientist to develop high-quality markers from dense satellite imagery across agriculture, land management, and climate. You will collaborate with scientists and engineers to deploy models at scale and contribute to embeddings-based insight extraction.

The role is full-time and hybrid, requiring presence in Haarlem, Graz, or Ljubljana three days per week. You will work with multi-sensor Earth observation data to solve environmental challenges and report on progress.

Qualifications

• 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 clean, maintainable code.
• Experience with AI agents and modern ML tools.

Responsibilities

• Develop algorithms and ML models to extract insights from satellite imagery time series.
• Take research topics from exploration through production.
• Own marker results for production deliveries across EU countries and ensure quality before client delivery.
• Collaborate to deploy models at scale and expand into new areas.
• Document and communicate results through internal reports and client-facing outputs.

Skills

Python programming

English proficiency

Machine learning

Git/version control

Geospatial domain knowledge

Education

Bachelor's degree in CS/Data Science

Tools

Git

Job description

Planet is seeking a Data Scientist to develop high-quality markers from dense satellite imagery across agriculture, land management, and climate. You will collaborate with scientists and engineers to deploy models at scale and contribute to embeddings-based insight extraction.

The role is full-time and hybrid, requiring presence in Haarlem, Graz, or Ljubljana three days per week. You will work with multi-sensor Earth observation data to solve environmental challenges and report on progress.