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

Location not identified

Pay
$83,000–87,000/yearAnnual period assumed — pay source
Pay Range $83,000.00 to $87,000.00 depending on experience, education, and clearance level.
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Work setup
Unconfirmed
Employment
Unconfirmed
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What you’ll work on

Full posting
  • 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

  • Design, execute, and analyze convective- and meso-scale modeling experiments using high-performance computing (HPC) resources

From the employer’s posting
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
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
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

What you’ll bring

All qualifications

Core experience

  • 8+ years of professional or academic experience
  • 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
  • Experience utilizing complex modeling systems in high-performance computing (HPC) environments
Qualification wording
8+ years of professional or academic experience
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
Experience utilizing complex modeling systems in high-performance computing (HPC) environments
Education & alternatives
Required: - MS Degree (PhD Preferred) in meteorology, atmospheric science, computer science, engineering, or a related field - 8+ years of professional or academic experience

Tools in this posting

  • Bash
  • Python
Source — Tool mentions in context
- 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
- 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

Job description

View original posting ↗

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.

 

Work Schedule and Location:

 

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

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

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

Qualifications

Required: 

  • 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:

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Long-term and Short-term Disability Insurance
  • Life Insurance
  • 401(k) Plan
  • Holiday Pay
  • Paid Time Off

Pay Range

$83,000.00 to $87,000.00 depending on experience, education, and clearance level. 

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on careers-fedwriters.icims.com. The employer’s form will show what is required.

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Source & posting history

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Source notes

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Pay
Pay Range $83,000.00 to $87,000.00 depending on experience, education, and clearance level.
Location & working pattern

Location not supplied.

Work Schedule and Location: Remote: This full-time remote position will work Monday through Friday, 8 AM CST to 5 PM CST. FWI is expanding rapidly and has been recognized as a 2024, 2025 and 2026 Top Workplace, offering excellent growth opportunities in a collaborative environment.
More source context
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
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Sep 3, 2026
Recorded sightings
61
Last seen by us
Oct 9, 2026

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