Benefits:- Opportunity for advancement
- Training & development
- 401(k)
- 401(k) matching
- Bonus based on performance
- Competitive salary
- Flexible schedule
PEMDAS® Technologies & Innovations is seeking an Atmospheric Scientist to support applied research and development across weather analysis, forecasting, remote sensing, and decision-support tools. The ideal candidate combines strong scientific knowledge with programming and data-analysis skills, and can turn complex atmospheric data into practical insights for operational users.
What You’ll Do
- Analyze atmospheric and environmental data from radar, satellites, surface observations, soundings, and numerical weather prediction models.
- Develop and evaluate methods, algorithms, and tools for forecasting, nowcasting, and severe-weather analysis.
- Use Python and other scientific programming languages to process, visualize, and interpret large datasets.
- Apply statistical methods and machine learning to improve forecasts, diagnostics, and decision-support capabilities.
- Support model evaluation, validation, and verification using observational data.
- Collaborate with scientists, engineers, and operational partners on applied research and research-to-operations efforts.
- Present findings through technical reports, briefings, and clear documentation for both technical and nontechnical audiences.
- Contribute to project planning and deliver high-quality work on schedule.
Required Qualifications
- Bachelor’s degree in meteorology, atmospheric science, or a closely related field; a master’s degree or Ph.D. is preferred.
- Experience analyzing atmospheric data and interpreting weather systems.
- Proficiency in Python or another scientific programming language.
- Experience with numerical weather prediction, remote sensing, radar, satellite, or observational datasets.
- Strong written and verbal communication skills.
- Ability to work independently and collaboratively in a remote, multidisciplinary team.
Preferred Qualifications
- Graduate-level education or equivalent applied research experience in atmospheric science or meteorology.
- Experience with machine learning, statistical analysis, or scientific algorithm development.
- Familiarity with tools such as xarray, NumPy, pandas, scikit-learn, PyTorch, ArcGIS, or QGIS.
- Experience with Linux, cloud-based data, high-performance computing, or operational forecasting environments.
- Peer-reviewed publications, conference presentations, or experience translating research into operational applications.
Work arrangement: Remote
Compensation: Competitive and based on experience
This is a remote position.