GDHydrology Data Support Scientist

Come see your career take flight at NASA.

This Hydrology Data Support Scientist position requires a motivated and capable scientist to provide end-to-end support for the Goddard Earth Sciences Data and Information Services Center (GES DISC) to facilitate our mission in support of NASA earth data products related to hydrologic precipitation and water-related remotely sensed products using the suite of NASA satellites. These data products include legacy, current and future NASA Earth Science mission data (satellite and modeling), and discipline-related products.

For more information about the GES DISC please visit our web site ((Use the "Apply for this Job" box below).).

Data Support Scientist responsibilities will include understanding the currently archived data at GES DISC (data formats and associated metadata), developing scientific applications such as algorithms for generating value-added products and applications to support advanced services that can be plugged into existing visualization and analysis systems, and developing tools to support interoperability for discovering, accessing, customizing, viewing, and analyzing data. We highly prefer applicants with a strong background in applied sciences who can effectively translate theoretical research into practical, real-world water management solutions.

While prior experience using hydrological models is encouraged, it is not strictly required. A critical requirement for this role, however, is the ability to leverage satellite and remote sensing datasets to perform robust analyses using programming languages such as Python. Typical responsibilities will include developing applied hydrological use cases and publishing scientific articles to effectively communicate research outcomes to the broader community.

Position responsibilities will also include developing extensive documentation on the data products and services, providing user-focused support, and supporting the GES DISC user outreach efforts. An example of value added support services is our Giovanni web based visualization tool ().

The Hydrology Data Support Scientist applicant is expected to solve complex algorithm or data conversion problems with little or no oversight and have the ability to respond effectively to science data user questions on technical and scientific issues, provide technical and scientific support in enhancing and extending data and information services. As such, excellent communication skills (written and oral) are a must.

The candidate will also have demonstrated capability and interest to learn and apply new technologies to tasks at hand and commensurate familiarity with common data formats, data analysis tools, and relevant programming languages (HDF/HDF-EOS, GRADS, netCDF, IDL, Python, Perl, Fortran,

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• M.S./B.S. in Earth or Environmental Sciences, hydrology, civil engineering, or related physical or atmospheric related science, engineering
• Satellite remote sensing experience with 3+ years hands on experience supporting satellite based mission data and products
• 4+ years related experience; scientific programming experience and skill with use of languages such as (Python, IDL, GRADS, perl, C, Fortran) and data formats HDF/HDF-EOS
  , HDF5, netCDF4, GRIB, and metadata
• Excellent inter-personal and communications skills
• Motivated individual with a keen sense for problem solving and ability to work with little supervision and as part of a team
• Experience leading small projects from inception through execution
• Ability to work in a multi-task environment
• US Citizenship or Permanent Residency (LPR) required, with residency in the US for the past consecutive 3 years is required.
• Ability to obtain and maintain a Tier 1 or Tier 2 Investigation through NASA.
• Experience in an operational data center or with large data storage systems
• Self motivated individual with experience or interest in leading projects
• Experience with proposal writing and development is plus
• Familiarity with UNIX/Linux environment
• Experience visualizing scientific data or presentation of data for outreach or to a larger user community