Atmospheric Scientist

BLUE STORM ASSOCIATES INC

2d•Remote

About The Position

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 scientific knowledge with programming and data-analysis skills to translate complex atmospheric data into practical insights for operational users. The position is remote and involves collaboration with scientists, engineers, and operational partners on applied research and research-to-operations efforts. Compensation is competitive and based on experience.

Requirements

Bachelor’s degree in meteorology, atmospheric science, or a closely related field.
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.

Nice To Haves

A master’s degree or Ph.D.
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.

Responsibilities

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 technical and nontechnical audiences.
Contribute to project planning and deliver high-quality work on schedule.