This role is for one of the Weekday's clients

We are looking for a highly skilled Remote Sensing Engineer with a strong background in remote sensing technologies, geospatial analysis, and image processing. In this role, you will work with large-scale satellite and aerial imagery datasets to develop innovative solutions for environmental monitoring, land-use mapping, and various geospatial applications. Your expertise in remote sensing algorithms, data interpretation, and processing techniques will drive insights that support critical decision-making.

Key Responsibilities

•  Data Acquisition & Processing: Collect, process, and analyze remote sensing data from multiple sources, including satellite, UAV, and LiDAR.
•  Image Processing & Analysis: Apply advanced image processing techniques such as classification, object detection, and spectral analysis to extract meaningful insights.
•  Algorithm Development: Design and implement algorithms for feature extraction, land cover classification, and change detection using machine learning and deep learning techniques.
•  Geospatial Analytics: Perform geospatial data integration, interpretation, and visualization to support various applications such as agriculture, forestry, urban planning, and environmental monitoring.
•  Cloud & Big Data Processing: Work with cloud-based geospatial platforms and big data processing frameworks to handle large-scale remote sensing datasets efficiently.
•  Collaboration & Reporting: Work closely with cross-functional teams, including GIS specialists, data scientists, and software engineers, to develop and implement geospatial solutions. Present findings through reports, dashboards, and visualizations.

Required Skills & Qualifications

•  Experience: Minimum 5 years of experience in remote sensing, geospatial analysis, and satellite image processing.
•  Technical Expertise: Strong proficiency in remote sensing tools and platforms such as Google Earth Engine, ENVI, QGIS, ArcGIS, or equivalent.
•  Programming: Hands-on experience with Python, R, or MATLAB for geospatial data processing and analysis.
•  Machine Learning: Experience with machine learning models for image classification, segmentation, and pattern recognition.
•  Satellite & LiDAR Data: Knowledge of various satellite sensors, LiDAR data processing, and hyperspectral/multispectral image analysis.
•  Cloud Computing: Familiarity with cloud-based geospatial services (AWS, GCP, or Azure) for large-scale remote sensing data processing.
•  Visualization: Ability to create compelling visual representations of remote sensing data for decision-making.

Preferred Qualifications

• Master's or Ph.D. in Remote Sensing, Geospatial Science, Earth Observation, or a related field.
• Experience in deep learning for geospatial applications using TensorFlow or PyTorch.
• Knowledge of Synthetic Aperture Radar (SAR) data processing.
• Understanding of GIS data formats and spatial databases.