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Scientific Data Manager
URL: https://jobs-css.icims.com/jobs/2138/scientific-data-manager/job
Company / Organization: NOAA National Ocean Service (NOS)
Type: Full-time
Description:
NOAA's National Ocean Service (NOS) is responsible for the health and safety of our nation's coastal and oceanic environment. The Information and Technology Branch within the NCCOS Business Management Division requires a Scientific Data Manager to steward existing and new scientific data, metadata, and other associated documentation for the Marine Spatial Ecology Division (MSE) Biogeography Branch. The position will fulfill immediate requirements for managing data as part of a Natural Resource Damage Assessment (NRDA) project for mesophotic and deep coral restoration in the Gulf of Mexico. This position is for a Scientific Data Manager familiar with stewarding and cataloging environmental data, including hydrographic surveys, biological and physical observations, video and photographic data, geospatial data products (i.e., GIS layers), and model output. The successful applicant will coordinate with NCCOS scientists, data managers, software developers, and other federal offices to identify and use existing software and hardware tools for organizing, storing, sharing, and tracking datasets.
Requirements:
• Two or more years of professional experience with scientific data management beyond the requirements for academic training; experience with publishing datasets • A bachelor's degree in biological sciences, data science, or equivalent is required • Knowledge of database structure and theory; attention to detail with outstanding organizational and time-management skills • Knowledge of environmental data management, including policies and procedures for data collection, ship-to-shore data management, analytical data management, data cataloguing • Experience or training in ArcGIS, geodatabase design, scientific video, seafloor imagery (e.g., MBES, sidescan, photo mosaics), hydrographic survey data (e.g., .all, .bag, .xtf), a variety of spatial data formats (e.g., NetCDF, HDF, etc.), Python, SQL, Metadata, R, are desirable.
Point of Contact: Amber Batts
