Data Fusion Scientist

GalaxEye Space is building the next generation of Earth Observation (EO) satellites with a unique multi-sensor payload integrating Synthetic Aperture Radar (SAR, X-band) and Multi-Spectral Imager (MSI) capabilities. Our mission is to deliver unprecedented, high-fidelity, all-weather, all-time data products. High-precision coregistration serves as the foundation for our flagship SyncFused product (SAR + MSI fusion).

Role Overview

Data Coregistration Scientist

Key Responsibilities

1. Multi-Sensor Coregistration & Geometric Integrity

• Design and implement high-precision coregistration algorithms for multi-modal sensor data.
  

• Address geometric distortions and radiometric normalization challenges inherent in SAR and MSI datasets.
  

• Develop robust pipelines for georeferencing, orthorectification, and co-registration across large areas.
  

• Collaborate with sensor and ground-segment teams to define and execute Cal/Val procedures.
  

2. Data Preparation for Fusion

• Build automated pipelines for geometrically and radiometrically corrected multi-sensor datasets.
  

• Develop resampling and projection methods that preserve sensor-specific characteristics.
  

• Continuously refine methods to maximize spatial and temporal alignment accuracy.
  

3. Algorithm Development & Validation

• Write clean, optimized, scalable code suitable for cloud-based deployment.
  

• Design and run rigorous validation experiments to quantify accuracy and reliability of outputs.
  

4. Documentation & Collaboration

• Maintain detailed technical documentation of algorithms, methodologies, and validation results.
  

• Stay updated with advancements in remote sensing, geometric modeling, and sensor research.
  

• Collaborate with Data Fusion Scientists, Remote Sensing Analysts, and Software Developers for pipeline integration.
  

Education:

Experience:

Technical Expertise:

• Strong understanding of SAR data processing (speckle reduction, radiometric correction, geometric modeling).
  

• Experience with geometric and feature-based image registration techniques for multi-modal data.
  

• Expert proficiency in Python (NumPy, SciPy, Pandas, GDAL/Rasterio, Scikit-image/OpenCV).
  

• Knowledge of sensor models (RPCs, rigorous models) and advanced georeferencing techniques.
  

• Experience with parallel or distributed computing is a strong plus.
  

Preferred Qualifications

• Experience using computer vision or deep learning for automated feature matching/registration.
  

• Publications or project contributions in multi-sensor geometric correction or coregistration.
  

• Familiarity with EO tools such as SNAP or ENVI.