Job description

Purpose of the Position: The Research Scientist II will serve as task lead over various processes and be responsible for data analysis, extracting, validating, and cataloguing vital metadata from complex, large-scale Earth Science NASA scientific data collections. Minimum Requirements: • Master's Degree in a relevant scientific field or an equivalent combination of education and years of work experience. • 1 to 2 years of full-time verifiable work experience (preferably in science, engineering, business, or equivalent). • Proficiency in Python or other programming languages. • Familiarity with common scientific data formats, such as gridded data like NetCDF or HDF5 • Ability to document workflows clearly and communicate technical concepts to both scientific and engineering team members • Knowledge of MS Office Suite Desired Qualifications: • Foundational knowledge or hands-on experience with Amazon Web Services (AWS) environments (e.g., S3 storage, EC2, Lambda). • Experience with GIS software (ArcGIS, QCIS) or geospatial libraries (GDAL/OGR, Rasterio, Geospandas) • Organizational skills and an eye for detail, essential for catching inconsistencies in vast datasets • Familiarity with Git and GitHub for code sharing and collaboration Published Salary (if available): $67,151 - $89,611

Requirements

Must-haves

Master's Degree in a relevant scientific field or an equivalent combination of education and years of work experience.
1 to 2 years of full-time verifiable work experience (preferably in science, engineering, business, or equivalent).
Proficiency in Python or other programming languages.
Familiarity with common scientific data formats, such as gridded data like NetCDF or HDF5
Ability to document workflows clearly and communicate technical concepts to both scientific and engineering team members
Knowledge of MS Office Suite
$67,151 - $89,611

Nice-to-haves

Foundational knowledge or hands-on experience with Amazon Web Services (AWS) environments (e.g., S3 storage, EC2, Lambda).
Experience with GIS software (ArcGIS, QCIS) or geospatial libraries (GDAL/OGR, Rasterio, Geospandas)
Organizational skills and an eye for detail, essential for catching inconsistencies in vast datasets
Familiarity with Git and GitHub for code sharing and collaboration

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonaws

Platform: pageup
Effort: medium