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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