Geospatial Analyst, MethaneSAT Science

The Remote Sensing team at Environmental Defense Fund (EDF) is seeking a Geospatial Analyst with proven geospatial analytical and research skills in support of a major satellite mission to assess methane emissions with a focus on the global oil and gas sector using geospatial data and analytics. This is a 3-year fixed-term position with opportunity for extension. Key Responsibilities: Create automated geoprocessing workflows and conduct geospatial, statistical, and other advanced data analyses for EDF/MethaneSAT's methane emission assessment, methane inventory development, and methane source attribution work, and prepare data visualizations and reports of findings. Compile, integrate, and analyze multiple and disparate geospatial datasets, including methane emissions data and oil and gas and non-oil and gas activity data reported in peer-reviewed publications and by governments and companies to support the development of robust analytics on global oil and gas methane emissions. Perform data and geospatial analytics of the MethaneAIR and MethaneSAT observations and geospatial targets development. Ensure high degree of confidence in the projects' data products including the development and implementation of QA/QC strategies regarding methane emissions characterization and source attribution analytics. Support and manage key components of ongoing projects with internal and external partners, including from academia, industry, and research organizations. Perform literature reviews and analyze and synthesize scientific/technical information on a variety of topics to support MethaneSAT project and related EDF activities. Required Qualifications: Bachelor's degree with at least 2 or more years of relevant experience or a Master's degree in Geoinformation Science and Analytics, Environmental Science, Geospatial Technologies, Geography, Earth Systems Science, Remote Sensing, or a related discipline. Strong quantitative background in geospatial data analytics and tools (e.g., ArcGIS, QGIS, geostatistics). Proficiency in programming languages is desired (Python preferred), and experience working with large geospatial and satellite datasets is highly desired.