Remote Sensing and Earth Observation Specialist

Company: COTESA Description: Do you enjoy researching, developing, and testing novel remote sensing methodologies? From data to model—and model to validation—you’ll combine your scientific foundation with programming and geospatial analysis in applied R&D projects focused on agriculture, water resources, and the environment. We are looking for a remote sensing specialist with a strong scientific background and experience in programming and geospatial analysis. WHAT YOU’LL DO & PROJECTS YOU’LL JOIN: You will contribute to the development of remote sensing and Earth observation solutions, participating in the design, implementation, and validation of methodologies that transform satellite, meteorological, and other geospatial data into products, indicators, and models. DAILY RESPONSIBILITIES: Develop data acquisition, preparation, and processing workflows, integrating multiple data sources and working with large volumes of geospatial data. Analyze satellite imagery and time series using spectral and multispectral analysis techniques. Develop and validate physical, statistical, and machine learning models for tasks such as estimation, classification, segmentation, object detection, change detection, and anomaly identification. Evaluate methodology and model outputs using appropriate statistical metrics and validation procedures tailored to each application. Participate in R&D projects, contributing to the creation of robust, reproducible, and scalable solutions. Your work may support applications in: agriculture and vegetation, water resources, environment, atmosphere and climate, land and infrastructure, natural hazards, and emergency management. REQUIRED KNOWLEDGE & EXPERIENCE: Remote Sensing: Strong scientific foundation and comprehensive understanding of the discipline, including physical principles, data acquisition and processing, sensor characteristics, and interpretation of Earth observation data. Satellite Sensors: Experience with Sentinel-2 and Landsat; additional experience with Sentinel-1 (SAR), Sentinel-3, and other sensors is valued. Python Programming: Intermediate-level Python proficiency with hands-on experience using NumPy, Pandas, PySTAC, Xarray, Rasterio, GeoPandas, and GDAL. Geospatial Processing: Ability to perform reprojections, resampling, masking, mosaicking, and working with coordinate systems, raster, and vector data. Spectral Analysis: Knowledge of vegetation index calculation, multispectral analysis, and time series processing. Open Data Sources & Repositories: Familiarity with major open Earth observation platforms, repositories, and datasets; ability to locate, query, select, and retrieve appropriate data for diverse applications. Machine Learning: Understanding of regression, classification, Random Forest, XGBoost, and model validation using statistical metrics. Development Tools: Experience with QGIS, Git, and Python development environments. Satellite Data Access: Familiarity with STAC catalogs and processing of large-scale geospatial datasets. ADDITIONAL SKILLS WE VALUE: Object-oriented programming, class and method management. Deep learning for satellite imagery (e.g., PyTorch). Processing of thermal, SAR, and LiDAR data. Techniques for image super-resolution or downscaling (optical or thermal). Scalable processing with Dask, Zarr, and cloud tools. Radiative transfer models (e.g., PROSPECT, SAIL) and bio-physical parameter estimation. EDUCATION: Degree or background in remote sensing, geospatial technologies, physics, geomatics/geodetic engineering, geography, agricultural engineering, computer science, or related fields. WHAT WE OFFER: Flexible working hours and remote work options to support your daily routine. Intensive summer working schedule for more personal time. Flexible compensation plan to tailor part of your salary to your needs. Participation in high-impact national and international technological projects. Innovative environment at the intersection of GIS, Artificial Intelligence, and Earth Observation. Continuous training and professional development opportunities. Collaboration with a highly specialized, multidisciplinary team. Autonomy to lead projects and contribute new ideas.