Remote Sensing Scientist - Agricultural Applications
Our client is seeking a highly motivated and experienced Remote Sensing Scientist to join their fully remote team, focusing on agricultural applications. This role is pivotal in leveraging satellite and aerial imagery, along with other geospatial data, to provide critical insights for crop monitoring, yield prediction, land use analysis, and environmental impact assessment. The successful candidate will have a strong background in remote sensing principles, image processing, GIS, and a solid understanding of agricultural science. This is a remote-first position, offering the flexibility to work from anywhere within the US, requiring excellent communication and self-management skills.
Responsibilities:
Acquire, process, and analyze multi-spectral, hyper-spectral, and thermal imagery from various satellite and airborne platforms (e.g., Landsat, Sentinel, Planet, drones). Develop and implement algorithms for vegetation indices, crop health assessment, land cover classification, and change detection relevant to agriculture. Integrate remote sensing data with other geospatial datasets (e.g., weather, soil, yield data) using GIS software for comprehensive analysis. Develop predictive models for crop yields, disease outbreaks, and water stress using machine learning and statistical techniques applied to remote sensing data. Collaborate with agronomists, data scientists, and software engineers to translate complex data into actionable insights for agricultural stakeholders. Create detailed reports, visualizations, and presentations to communicate findings to both technical and non-technical audiences. Contribute to the development of new methodologies and tools for agricultural monitoring and management using remote sensing. Stay current with the latest advancements in remote sensing technologies, algorithms, and applications in agriculture. Manage data storage, processing workflows, and ensure data quality and consistency. Participate in proposal development for new research and commercial projects. Required Qualifications:
Ph.D. or Master's degree in Remote Sensing, Geography, Environmental Science, Agricultural Science, Computer Science, or a related field with a strong focus on geospatial analysis. Minimum of 5 years of experience in applying remote sensing techniques to agricultural challenges. Proficiency in remote sensing software (e.g., ENVI, ERDAS Imagine, SNAP) and GIS software (e.g., ArcGIS, QGIS). Strong programming skills in Python, R, or similar languages for data analysis and algorithm development. Experience with cloud-based geospatial platforms (e.g., Google Earth Engine, AWS) is highly desirable. Knowledge of agricultural practices, crop physiology, and soil science. Experience with machine learning and statistical modeling for geospatial data. Excellent analytical, problem-solving, and critical thinking skills. Strong written and verbal communication skills, with the ability to present complex information effectively. Proven ability to work independently, manage multiple projects, and meet deadlines in a remote work environment. This role offers a unique opportunity to contribute to global food security and sustainable agriculture through cutting-edge technology, with the full benefits of a remote work arrangement.
Responsibilities:
Acquire, process, and analyze multi-spectral, hyper-spectral, and thermal imagery from various satellite and airborne platforms (e.g., Landsat, Sentinel, Planet, drones). Develop and implement algorithms for vegetation indices, crop health assessment, land cover classification, and change detection relevant to agriculture. Integrate remote sensing data with other geospatial datasets (e.g., weather, soil, yield data) using GIS software for comprehensive analysis. Develop predictive models for crop yields, disease outbreaks, and water stress using machine learning and statistical techniques applied to remote sensing data. Collaborate with agronomists, data scientists, and software engineers to translate complex data into actionable insights for agricultural stakeholders. Create detailed reports, visualizations, and presentations to communicate findings to both technical and non-technical audiences. Contribute to the development of new methodologies and tools for agricultural monitoring and management using remote sensing. Stay current with the latest advancements in remote sensing technologies, algorithms, and applications in agriculture. Manage data storage, processing workflows, and ensure data quality and consistency. Participate in proposal development for new research and commercial projects. Required Qualifications:
Ph.D. or Master's degree in Remote Sensing, Geography, Environmental Science, Agricultural Science, Computer Science, or a related field with a strong focus on geospatial analysis. Minimum of 5 years of experience in applying remote sensing techniques to agricultural challenges. Proficiency in remote sensing software (e.g., ENVI, ERDAS Imagine, SNAP) and GIS software (e.g., ArcGIS, QGIS). Strong programming skills in Python, R, or similar languages for data analysis and algorithm development. Experience with cloud-based geospatial platforms (e.g., Google Earth Engine, AWS) is highly desirable. Knowledge of agricultural practices, crop physiology, and soil science. Experience with machine learning and statistical modeling for geospatial data. Excellent analytical, problem-solving, and critical thinking skills. Strong written and verbal communication skills, with the ability to present complex information effectively. Proven ability to work independently, manage multiple projects, and meet deadlines in a remote work environment. This role offers a unique opportunity to contribute to global food security and sustainable agriculture through cutting-edge technology, with the full benefits of a remote work arrangement.