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# Junior Earth Observation & Geospatial Data Scientist

- **Company:** CinSOIL GmbH
- **Location:** Bremen, Germany (Remote available)
- **Experience:** Starter
- **Salary:** €42,000.0 - €50,000.0
- **Contract:** Permanent contract
- **Skills:** Geographic Information Systems, Algorithm Design, Databases, Data Cleansing, Linux, Python (Programming Language), Reference Data, Spatial Data Infrastructures, Git, Software Version Control
- **Published:** August 10, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=5d8006bcf81ee288

## About the Role

* Degree (or near-complete) in geoinformatics, remote sensing, environmental science, data science, or similar

 * Solid Python skills, including exposure to geospatial libraries (e.g. rasterio, geopandas, xarray, shapely)

 * Familiarity with satellite EO data (Sentinel mission in particular)

 * Understanding of basic remote sensing concepts

 * Comfortable working in a Linux/bash environment and with version control (Git)

 * Eagerness to learn and grow into a more senior EO role over time

Nice to have:

 * Experience with openEO or similar cloud EO processing frameworks

 * Familiarity with STAC catalogues and cloud-optimised data formats (COG, Zarr)

 * Prior project or thesis work involving time series methods applied to geospatial data

 * Knowledge of agricultural applications of EO or land surface monitoring

## Description

You will join our EO analytics team and support the development, maintenance, and quality assurance of geospatial data pipelines, working closely with our Senior EO Data Scientist. You will get hands-on with real satellite data and production pipelines from day one, with plenty of room to grow into more independent ownership as you build experience.

This position is contingent on the finalisation of an upcoming ESA contract, whose deliverables involve close collaboration with the contract's stakeholders.

What You'll Work On

 * Supporting the development and maintenance of Python-based pipelines for processing satellite imagery at scale

 * Running and QA-ing time series analysis of multispectral and SAR data over agricultural areas

 * Data preparation, validation, and documentation for algorithm development

 * Spatial data management using geospatial libraries and databases

 * Contributing to testing and validation against ground reference data


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