Weather Forecast Modeling Scientist

MPAS-JEDI is the backbone of NSSL's next-generation convective-scale modeling and data assimilation work — and it needs someone who can keep the software, the science, and the HPC infrastructure all moving together. As FWI's MPAS-JEDI Systems and Convective-Scale Modeling Specialist, you will develop, install, and support MPAS-JEDI and related modeling/data assimilation systems across HPC, cloud, and operational computing platforms, supporting WoFS and WoFSCast research and operational transition.

You'll be equally at home writing Python/Fortran workflow tools and diagnosing a storm-scale forecast bust.

Work Schedule and

Location:

Hybrid:
This full-time hybrid position will work Monday through Friday, 8 AM CST to 5 PM CST, with 90% at National Severe Storms Laboratory (NSSL), National Weather Center, Norman, Oklahoma, or designated field deployment locations.

FWI is expanding rapidly and has been recognized as a 2024, 2025 and 2026 Top Workplace, offering excellent growth opportunities in a collaborative environment.

• Develop, install, maintain, and support MPAS-JEDI and related atmospheric modeling and data assimilation systems on HPC, cloud, and operational computing platforms
• Develop and maintain scientific software, workflows, and automation tools using Python, Bash, Git, Fortran, and related technologies
• Implement and support real-time and retrospective modeling workflows using workflow management systems such as EC-Flow, Rocoto, or similar frameworks
• Support ensemble-based data assimilation, numerical weather prediction, software integration, testing, version control, and operational transition activities
• Manage, organize, and validate large modeling and observational datasets supporting WoFS, WoFSCast, MPAS-JEDI, and ML/AI applications
• Conduct model verification, diagnostics, quality control, and forecast evaluation using METplus and related verification frameworks
• Design, execute, and analyze convective- and meso-scale numerical experiments focused on storm-scale forecasting and data assimilation applications
• Collaborate with scientists, students, software engineers, and operational partners to resolve technical issues and advance forecasting capabilities
• Prepare technical documentation, reports, presentations, and scientific publications supporting project and research objectives

Required:

• MA/MS (PhD. Preferred) in meteorology, atmospheric science, computer science, engineering, applied mathematics, or a related field
• 8+ years of relevant professional or academic experience

Desired:

• Experience with convective- and/or meso-scale numerical weather prediction and ensemble-based data assimilation systems
• Proficiency in Python, Bash, Git, and scientific software development in HPC environments
• Familiarity with MPAS-JEDI, JEDI, WoFS, WoFSCast, MPAS, WRF, or similar modeling and data assimilation frameworks
• Experience with operational workflow management systems (e.g., EC-Flow, Rocoto) and large atmospheric modeling and observational datasets
• Knowledge of storm-scale forecasting, forecast verification methodologies, model diagnostics, and quality control procedures, including tools such as METplus
• Demonstrated ability to collaborate effectively within multidisciplinary teams and communicate technical and scientific results through presentations, reports, and peer-reviewed publications

Work Setting and Environment:

• Primary location:
  National Severe Storms Laboratory (NSSL), National Weather Center, Norman, Oklahoma, or designated field deployment locations
• Normal work hours are Monday through Friday, 8 hours per day / 40 hours per week, excluding federal holidays; field data-collection activities may require irregular hours during active severe weather events
• Remote work arrangements must be reviewed and approved in advance by the Contracting Officer's Representative (COR); on-site presence may be required based on mission, field operations, collaboration, or security needs
• Local and non-local travel may be required, not anticipated to exceed 5% annually; all unplanned travel must be approved in writing by the COR at least 10 calendar days in advance
• Must complete an online IT security awareness course within one week of starting work
• Foreign national candidates are subject to export control review and require CO/COR approval prior to consideration
• Government-furnished equipment provided, including access to HPC resources, specialized mobile observation platforms, laboratory test equipment, computers, and…