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

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Satellite Data Assimilation and Fire Weather Modeling Specialist (Scientist IV) based in United States.

This role offers the opportunity to advance next-generation atmospheric modeling for fire weather, smoke, and aerosol prediction.
You will develop and enhance convective- and meso-scale modeling systems using frameworks such as MPAS and WRF.
Your work will integrate satellite and in-situ observations through advanced ensemble-based data assimilation techniques.
You will use high-performance computing to conduct complex modeling experiments and improve forecast accuracy.
Your research will help strengthen understanding and prediction of interactions between fire, weather, smoke, and atmospheric aerosols.
Working alongside multidisciplinary scientific teams, you will contribute to research with direct operational relevance for weather and fire forecasting.
The position also provides opportunities to publish research, present findings, and influence the development of future fire and smoke forecasting capabilities.

Accountabilities

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

Requirements

• A Master’s degree in meteorology, atmospheric science, computer science, engineering, or a related field is required; a PhD is preferred.
• At least 8 years of professional or academic experience in a relevant scientific, technical, or research environment is required.
• Demonstrated experience with convective-scale and/or meso-scale numerical weather prediction modeling is highly desirable.
• Strong knowledge and practical experience with ensemble-based data assimilation techniques are preferred.
• Experience in fire, smoke, and/or aerosol modeling and prediction is highly desirable.
• Demonstrated ability to modify and develop scientific code within MPAS, WRF, or comparable atmospheric modeling frameworks is preferred.
• Advanced programming skills in Python, Bash, Fortran, Git, and related scientific computing technologies are desirable.
• Experience working with complex atmospheric modeling systems in high-performance computing environments is preferred.
• Understanding of aerosol, fire, and smoke parameterization schemes and their implementation within numerical models is highly desirable.
• Strong analytical skills and the ability to evaluate observational and model datasets to improve scientific and forecasting outcomes are expected.
• Demonstrated ability to communicate complex scientific results through technical reports, presentations, and peer-reviewed publications is preferred.
• Strong collaboration and communication skills, with the ability to work effectively within interdisciplinary research and development teams, are required.
• The position is fully remote, with standard working hours Monday through Friday, 8:00 AM to 5:00 PM Central Standard Time.
• Field data-collection activities may occasionally require irregular working hours during active severe weather events.
• Limited travel may be required, with travel expected not to exceed approximately 5% annually.
• Foreign national candidates are subject to applicable export control review and require appropriate approval before consideration.
• Candidates must complete an online information technology security awareness course within one week of starting the position.

Benefits

• Annual salary range of $83,000 to $87,000 .
• Health insurance.
• Dental insurance.
• Vision insurance.
• Short-term and long-term disability insurance.
• Life insurance.
• 401(k) retirement plan.
• Paid holidays.
• Paid time off.
• Government-furnished equipment and access to applicable high-performance computing resources, specialized observation platforms, laboratory equipment, computers, and office workspace.
• Opportunities for professional development, internal career advancement, recognition, and rewards programs.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.