Telespazio Belgium

Data Scientist, EO

Telespazio Belgium

full-time

Posted on:

Origin:  • 🇱🇺 Luxembourg

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Job Level

Mid-LevelSenior

Tech Stack

CloudDockerKubernetesNumpyPandasPythonPyTorchRemote SensingScikit-LearnTensorflow

About the role

  • Play a crucial role in EO-related projects under technical and operational constraints.
  • Analyze and process multi-source EO data (satellite imagery, LiDAR, drone datasets) to extract insights.
  • Develop and validate machine learning models for classification, detection, segmentation, or prediction using EO data.
  • Design and implement scalable and reproducible EO data processing pipelines (from ingestion to inference).
  • Contribute to the development of Max-ICS by designing and implementing generic AI models and reusable data processing pipelines and proposing new analytical features.
  • Collaborate with engineers to optimize EO data storage and retrieval and ensure AI model reproducibility and traceability.
  • Engage with stakeholders to understand requirements and deliver actionable, data-driven products.
  • Produce technical reports, models, documentation, and contribute to scientific publications.
  • Stay up to date with latest research and technologies in EO, remote sensing, and AI.
  • Communicate effectively across teams and provide training/support to colleagues or partners on EO data and analytical tools.

Requirements

  • Master's degree or PhD in Remote Sensing, Geoinformatics, Computer Science, Data Science, or a related field.
  • 3+ years of experience applying AI/ML to EO or geospatial data.
  • Experience with image processing techniques and libraries (e.g., OpenCV, scikit-image) for feature extraction, enhancement, and computer vision tasks.
  • Experience with time series analysis and spatio-temporal modeling is a strong asset.
  • Solid understanding of remote sensing principles and data formats (Sentinel, Landsat, SAR, etc.).
  • Strong proficiency in ML, Deep learning and Python libraries (NumPy, Pandas, scikit-learn, TensorFlow, PyTorch, geopadas).
  • Hands-on experience with MLOPS tools and workflows (e.g., MLflow, DVC, model versioning) is highly desirable.
  • Familiarity with cloud-based or distributed computing environments (S3, Kubernetes, Docker, GitLab CI/CD) is an asset.
  • Fluent in English; French is an asset.
  • Candidate must be eligible for EU security clearance.