Satellite Data Assimilation and Fire Weather Modeling Specialist (Scientist IV)

FWI (FedWriters, Inc.)

United States

On-site

USD 83,000 - 87,000

Full time

14 days+

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Benefits offered by this job

Health Insurance

Dental Insurance

Vision Insurance

Disability Insurance (long-term &短)

Life Insurance

401(k) Plan

Holiday Pay

Paid Time Off

Job summary

FWI is seeking a Satellite Data Assimilation and Fire Weather Modeling Specialist to advance MPAS/WRF-based systems for WoFS. You will integrate satellite and in-situ data within ensemble data assimilation to improve fire behavior, smoke transport, and aerosol forecasts.

The role demands 8+ years of experience, strong coding skills (Python, Bash, Fortran, Git), and experience with HPC environments. Expect remote, full-time work with collaboration across multidisciplinary teams.

Qualifications

MS Degree (PhD Preferred) in meteorology, atmospheric science, computer science, engineering, or a related field.
8+ years of professional or academic experience.

Responsibilities

Develop, modify, and maintain components of advanced atmospheric modeling systems within MPAS and/or WRF frameworks.
Implement and evaluate ensemble-based data assimilation methodologies for integrating satellite and in situ observations into fire, smoke, and aerosol prediction systems.
Conduct research and development activities to improve fire behavior, smoke transport, and aerosol parameterizations in numerical weather prediction models.
Design, execute, and analyze convective- and meso-scale modeling experiments using high-performance computing (HPC) resources.
Develop workflows and software tools using Git, Python, Bash, Fortran, and related technologies to support model development, testing, and evaluation.
Analyze model performance and observational datasets to identify opportunities for improving forecast skill and physical representation of fire-atmosphere processes.
Collaborate with multidisciplinary research teams to support development of next-generation fire and smoke forecasting capabilities.
Prepare technical documentation, code repositories, validation reports, and workflow descriptions to support research and operational activities.
Contribute to project reporting requirements, including quarterly and annual progress reports.
Lead or contribute to peer-reviewed scientific publications and present research findings at national and international conferences, workshops, and stakeholder meetings

Skills

Convective-scale modeling

Meso-scale modeling

Ensemble-based data assimilation

Fire and smoke modeling

High-performance computing

Code development

Scientific communication

Education

MS Degree (PhD Preferred) in meteorology, atmospheric science, computer science, engineering, or related field

Tools

MPAS

WRF

Python

Bash

Fortran

Git

Job description

Overview

As wildfires increasingly reshape the weather around them, NOAA needs modeling systems that can keep up. As FWI's Satellite Data Assimilation and Fire Weather Modeling Specialist supporting NSSL's Warn-on-Forecast (WoFS) initiative, you will develop and advance convective- and meso-scale atmospheric modeling systems — within the MPAS and/or WRF frameworks — that integrate satellite and in-situ observations through ensemble-based data assimilation to better predict fire behavior, smoke transport, and aerosol impacts. This is high-performance-computing science with real operational stakes: your work will help the National Weather Service better forecast how fire and atmosphere interact.

Overview

Work Schedule and Location:

Remote This full-time remote position will work Monday through Friday, 8 AM CST to 5 PM CST.

Responsibilities

Develop, modify, and maintain components of advanced atmospheric modeling systems within MPAS and/or WRF frameworks
Implement and evaluate ensemble-based data assimilation methodologies for integrating satellite and in situ observations into fire, smoke, and aerosol prediction systems
Conduct research and development activities to improve fire behavior, smoke transport, and aerosol parameterizations in numerical weather prediction models
Design, execute, and analyze convective- and meso-scale modeling experiments using high-performance computing (HPC) resources
Develop workflows and software tools using Git, Python, Bash, Fortran, and related technologies to support model development, testing, and evaluation
Analyze model performance and observational datasets to identify opportunities for improving forecast skill and physical representation of fire-atmosphere processes
Collaborate with multidisciplinary research teams to support development of next-generation fire and smoke forecasting capabilities
Prepare technical documentation, code repositories, validation reports, and workflow descriptions to support research and operational activities
Contribute to project reporting requirements, including quarterly and annual progress reports
Lead or contribute to peer-reviewed scientific publications and present research findings at national and international conferences, workshops, and stakeholder meetings

Required

Qualifications

MS Degree (PhD Preferred) in meteorology, atmospheric science, computer science, engineering, or a related field
8+ years of professional or academic experience

Desired

Experience with convective-scale and/or meso-scale numerical weather prediction modeling
Demonstrated expertise in ensemble-based data assimilation techniques
Prior experience in fire, smoke, and/or aerosol modeling and prediction
Proficiency modifying and developing code within MPAS, WRF, or similar atmospheric modeling frameworks
Advanced programming experience using Python, Bash, Fortran, Git, and related scientific software tools
Experience utilizing complex modeling systems in high-performance computing (HPC) environments
Understanding of aerosol, fire, and smoke parameterization schemes and their application within numerical models
Demonstrated ability to communicate scientific results through presentations, technical reports, and peer-reviewed publications
Ability to work effectively as part of an interdisciplinary research and development team

Work Setting And Environment

Primary location: Remote
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
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 office workspace, as applicable

Why Join Our Team

At FWI, we place the highest importance on creating an exceptional employee experience. You'll have opportunities to achieve your career aspirations through internal promotions, professional development, and other recognition and rewards programs. Join our team and take advantage of the many benefits we offer, including:

Benefits