Sixense Satellite, a subsidiary of VINCI Construction, is a leading player in satellite-based ground monitoring. We develop advanced technologies combining remote sensing, InSAR, and data science to deliver high-impact decision-support solutions for infrastructure management, natural hazard monitoring, and land-use planning.
As part of the VINCI Construction group, we help our clients better understand and anticipate ground deformation phenomena through Earth observation data and cutting-edge technologies.

Sixense Satellite is looking for a Data Scientist to join our team and contribute to the development of our Atlas InSAR (Interferometric Synthetic Aperture Radar) processing chain. You'll work on both maintaining and extending core processing capabilities, and on building new features that push our satellite-based ground deformation monitoring products forward.
This is a hands-on role for someone who wants to work at the intersection of remote sensing, geophysics, and applied machine learning.

Design and deploy machine learning models, including convolutional neural networks (CNNs),



for tasks such as phase unwrapping, atmospheric correction, anomaly/deformation detection, and signal classification
• Work with large volumes of SAR and interferometric data, building robust and scalable pipelines
• Collaborate closely with geophysicists, radar engineers, and software developers to translate research into production-ready tools
• iterate based on real-world performance
• Degree (MSc/PhD) in Data Science, Computer Science, Geophysics, Remote Sensing, Applied Mathematics, or a related field
• Experience in machine learning, with hands-on expertise in convolutional neural networks (CNNs) and deep learning frameworks (PyTorch, TensorFlow)
• Strong Python programming skills; experience with scientific computing libraries (NumPy, SciPy, xarray, etc.)
• Experience working with geospatial or remote sensing data (SAR/InSAR experience is a strong plus, but not mandatory)
• Co

📌 Data Scientist (España)
🏢 Sixense Iberia
📍 España