Senior Remote Sensing Data Scientist – GeoAI, Earth Observation
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Job Description
Remote Sensing Data Scientist focused on GeoAI services and digital agriculture projects. Developing ML/CV algorithms for processing remote sensing data in an international setting.
Responsibilities:
- Contribute to multiple geospatial AI and Earth observation initiatives.
- Focus on operationalisation of GeoAI services using AI and large-scale Earth observation processing.
- Support crop type mapping projects and scale algorithms for digital agriculture.
- Develop and improve ML/CV algorithms for large-scale remote sensing data processing on Sentinel data.
- Analyse data flows and optimise databases and queries.
- Collaborate with technical and non-technical stakeholders in an international setting.
Requirements:
- Aantoonbare ervaring in het optimaliseren en tunen van databases en queries.
- Aantoonbare ervaring met het analyseren van datastromen.
- Ability to operate in an international, multidisciplinary environment, with an excellent command of English.
- Volgens de aangeleverde informatie is Nederlands geen must-have voor deze opdracht.
- Proven experience with geospatial foundation models.
- At least 5-7 years of experience in developing and improving algorithms for large-scale remote sensing data processing.
- Knowledge of deep learning frameworks in PyTorch, with interest in applying them to geospatial or sensor data.
- Kennis van spatial databases, waaronder duckDB, en ervaring met de exploratie van noisy tabular labelled data.
- Een sterke software engineering achtergrond, met zeer goede Python-vaardigheden.
- Sterke GIS-vaardigheden, bijvoorbeeld met QGIS, ArcGIS en GDAL.
- Ervaring met tooling zoals dbt en Airflow.
- Taalvereiste zoals aangeleverd: Nederlandstalig op Europees CEFR-niveau C2.
- Aantoonbare ervaring met databanken zoals SQL en Oracle.
- Aantoonbare ervaring met rapportering.
- Aantoonbare ervaring met scripting, onder meer in Shell, Perl en Python.
- Proven academic credibility in the use of foundation models in remote sensing.
- Een zelfstandige werkhouding, sterke analytische vaardigheden en de communicatieve skills om technische en niet-technische stakeholders mee te nemen.
- Brede ervaring in het landbouwdomein is belangrijk, in het bijzonder voor crop type mapping en digitale landbouwtoepassingen.
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