Python Data Scientist Associate

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