Website U.S. Geological Survey
Climate change has broad and complex effects on natural systems, impacting everything from how plants grow to how often a region floods. Traditional management paradigms, which look to the past to guide decisions, are becoming less effective in this changing world. As a result, many resource stewards are searching for new and innovative tools to help guide their landscapes into the future. The National Climate Adaptation Science Center (NCASC) generates science and decision-making tools to help our nation respond to novel resource management challenges brought on by climate change.
The selected participant will co-develop standardized data management approaches and workflows for projects funded by the CASC network. Through this research experience, the fellow will have the opportunity to explore earth science community standards for the intake and publication of gridded data sets; contribute to the conversion of data holdings to cloud-optimized formats; and develop documentation of best practices for the handling of big datasets. The participant will assist with curating spatio temporal asset catalog (STAC) metadata and enhancing technical support for data visualizations of CASC data collections. This research will support scientists, data managers, and resource managers throughout the data lifecycle, by contributing to data accessibility and reuse.
Preferred Skills:
- Background and capability in data science and computing, including experience with multiple languages, frameworks, and technologies — such as Python, R, QGIS, GDAL, Git, or similar.
- Experience with processing and analysis of gridded data and cloud optimized data formats in Python – relevant libraries include xarray, zarr, dask, netCDF, fsspec.
- Knowledge of, and ability to implement, scientific metadata standards and protocols – familiarity with Climate and Forecast (CF) Metadata Conventions.
- Strong analytical, troubleshooting, and critical thinking skills.
- Ability to clearly communicate technical concepts, assess workflows, and prepare well-written documentation of methods.
- Knowledge of Quality Assurance / Quality Control as it applies to geospatial or climate data sets and analysis.
- Experience with relational databases, data manipulation, and data visualization.
- Knowledge of analysis ready, cloud optimized data formats and experience with reading and writing data in the cloud.
- Familiarity with Spatio Temporal Asset Catalogs (STAC).
- Ability to collaborate effectively and productively in digital collaboration and communication environments with teams of diverse professionals.
For more information and to apply: https://www.zintellect.com/Opportunity/Details/DOI-USGS-2024-15