Python Data Scientist Associate
Job description
SAIC is seeking an experienced Python Data Scientist Associate to support the development and maintenance of the Model Diagnostics Task Force (MDTF) framework, a unified system for selecting and instantiating standardized tasks for performing analysis on Earth system data. Our customer, NOAA GFDL, is the main developer of the MDTF framework with contributions from a consortium of government, academic, and private entities. This position requires an ability to obtain a Public Trust.
Desired physical location is in the Princeton, New Jersey or surrounding area.
Responsibilities include, but are not limited to:
Develop the framework using the established goals of the MDTF Leads Team as a guide create MDTF software upgrade and release plans ensure new code is well-documented and available to end users add new functionality and capabilities, coordinated by the MDTF Leads Team fix bugs and evaluate performance bottlenecks maintain CI/CD workflows for automated and manuatl testing/deployment develop unit tests for the framework maintain datasets as needed for the CI/CD and unit tests troubleshoot and consult on Data Catalog generation package and deploy new releases to the established PyPi distribution channel
Facilitate integration of a Jupyter Notebook-style interface for process-oriented diagnostics into the MDTF framework
Coordinate with GFDL’s Modeling Systems Division and Data Sciences Group developers as they integrate the MDTF framework into their respective workflows
Actively contribute to weekly multi-institutional development meetings
Bachelor’s degree in Computer Science, Information Systems, Engineering, Business or other related scientific or technical discipline
Experience in Systems Engineering or Programming
Experience in Python Programming
Strong Python skills (xarray, Jupyter notebook proficiency is a must)
Experience using and managing projects with git
Experience with version control and documentation, with an understanding of CI/CD fundamentals
Knowledge of CI/CD pipelines for automated workflows
Desirable Skills
Some basic knowledge of weather, ocean, or climate processes or a related science is preferred, but not necessary
Familiarity with cloud S3 storage
Familiarity with NetCDF dataset structures
Knowledge of AI and Machine Learning user agents (e.g. Gemini, Anthropic, OpenAI)
Knowledge of GitHub Actions CI/CD pipelines for automated workflows
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