Data Scientist

Planet; Graz; Hybrid; EUR 70.000 - 120.000; Vollzeit

Benefits dieser Stelle

Paid time off

Wellness program

Home office reimbursement

Monthly phone and internet stipend

Tuition reimbursement

Equity

Zusammenfassung

Planet is seeking a Data Scientist to develop high-quality markers from satellite imagery time series, enabling MSC analytics for EU CAP agencies. You will collaborate with scientists and engineers to deploy models at scale, exploring embeddings and AI-first workflows.

The role is full-time and hybrid, based in Graz/Ljubljana/Haarlem, with a strong emphasis on producing production-ready data products with clear documentation.

Qualifikationen

• 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.
• Proficiency in Python programming with readable, well-documented code.
• Experience with AI agents and modern ML tools.
• Experience with version control (Git) and collaborating 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.

Aufgaben

• Develop algorithms and ML models to extract insights from satellite imagery time series.
• Take research topics from exploration to production.
• Own marker results for production AMS deliveries across several EU countries.
• Explore embeddings-based insights in new areas beyond CAP.
• Use AI agents in daily work and improve team capabilities.
• Co-own the markers codebase with the team.
• Collaborate to build solutions on our platform and empower partners.

Kenntnisse

Python programming

Machine learning

Git

English

AI agents

Geospatial domain

Team collaboration

Ausbildung

Bachelor's degree or higher in CS/Data Science/STEM

Tools

Git

Cloud environments

Jobbeschreibung

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.

What You Bring:

• 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.

What Makes You Stand Out:

• 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.

Application Deadline:

11:45p / 23:45 CET on the date stated below. Applications are reviewed on a rolling basis. This posting may be removed earlier than projected if a suitable pool of applications has been received. For this reason, we recommend applying as soon as you are able to.

The application deadline for this role is December 13, 2026

Benefits While Working at Planet:

• 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

Compensation:

The expected starting gross salary range for this role is listed below. Individual placement within this range is determined objectively based on gender-neutral criteria such as your skills, qualifications, and professional experience. This position may also be eligible for discretionary bonuses and/or equity.

Austria Salary Range

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Why we care so much about Belonging.

We’re dedicated to helping the whole Planet, and to do that we must strive to represent all of it within each of our offices and on all of our teams. That’s why Planet is guided by an ultimate north star of Belonging-dreaming big as we approach our ongoing work. If this job intrigues you, but you’re thinking you might not have all the qualifications, please... do apply! At Planet, we are looking for well-rounded people from around the world who can contribute to more ways than just what is listed in this job description. We don’t just fill positions, we aspire to fulfill people’s careers, most excited about folks who are motivated by our underlying humanitarian efforts. We are a few orbits around the sun before we get to where we want to be, so we hope you’re excited to come along for the ride.

EEO statement:

Planet is committed to building a community where everyone belongs and we invite people from all backgrounds to apply. Planet is an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. Know Your Rights.

Accommodations:

Planet is an inclusive community and we know that everyone has their own needs. If you have a disability or special need that requires accommodation during the hiring process, please reach out to [e-mail] or contact your recruiter with your request. Your message will be confidential and we will be happy to assist you.

AI in Our Interviewing Process

Planet is committed to providing an exceptional interview experience for all candidates. We currently use Metaview to better focus on candidates and less on trying to capture notes. As such, with the candidate's consent, select interviews may be recorded and include a \"Planet AI Notetaker\" for transcription and summarization purposes. Should an interview involve use of AI interview technologies, the candidate will receive notification and have the ability to opt out both in advance and/or real-time. Opting out will not affect one's candidacy.

We understand that candidates may use various resources, including AI tools, to prepare for interviews and assessments. However, during any live interview stage or when actively completing assessments for this position, the use of AI tools- e.g. Large Language Models (LLMs), deep fake technology, etc.- is strictly prohibited unless explicitly prompted by an interviewer or assessment instructions.

Violation of this policy may result in disqualification of your application.