Data Scientist - InSAR & Earth Observation

VINCI; Barcelona; On-site; EUR 45,000 - 70,000; Full time

Job summary

Sixense Satellite, a VINCI Construction subsidiary, is seeking a Data Scientist to advance the Atlas InSAR processing chain. You will work at the intersection of remote sensing, geophysics, and applied machine learning to maintain and extend core capabilities and build new features.

The role involves designing CNN-based models for phase unwrapping, atmospheric correction, and deformation detection, plus deploying robust data pipelines for large SAR datasets. English fluency is required.

Qualifications

• MSc/PhD in a relevant field such as Data Science, Geophysics, or Remote Sensing.
• Hands-on experience with CNNs and deep learning frameworks.
• Strong Python skills and scientific computing libraries.
• Experience with SAR/InSAR data is a plus.
• Excellent English communication.

Responsibilities

• Design, develop, and optimize InSAR tools and processing chain.
• Implement new features to expand capabilities.
• Develop ML models (CNNs) for phase unwrapping, atmospheric correction, anomaly/deformation detection, and signal classification.
• Work with large volumes of SAR and interferometric data, building scalable pipelines.
• Collaborate with geophysicists, radar engineers, software developers to translate research into production tools.
• Validate model outputs against ground truth and domain knowledge.
• Document technical work and share knowledge internally.

Skills

Machine learning

CNNs

Python

Geospatial data

Data pipelines

Education

MSc/PhD in Data Science/Geophysics/Remote Sensing

Tools

PyTorch

TensorFlow

NumPy

SciPy

xarray

GIS tools

Job description

Sixense Satellite, a VINCI Construction subsidiary, is seeking a Data Scientist to advance the Atlas InSAR processing chain. You will work at the intersection of remote sensing, geophysics, and applied machine learning to maintain and extend core capabilities and build new features.

The role involves designing CNN-based models for phase unwrapping, atmospheric correction, and deformation detection, plus deploying robust data pipelines for large SAR datasets. English fluency is required.