Head of Atmospheric Research

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Establish scientific strategies for assessing atmospheric conditions, determining deployment timelines, analyzing results, and enhancing operational criteria.

• Incorporate forecasts, historical datasets, soundings, radar, satellite images, surface observations, and field-sensor data into scientific evaluations.

• Examine data prior to, during, and post-deployments; compare predicted versus observed conditions and convey conclusions along with uncertainties.

• Work alongside science, software, and field teams to refine observation techniques, enhance data quality, improve operational predictions, and conduct post-deployment analyses.

• Oversee the Weather Research and Forecasting (WRF) modeling initiative for planning deployments, atmospheric predictions, scenario assessments, and post-deployment evaluations.

• Design WRF data assimilation frameworks utilizing WRFDA, DART, or comparable systems.

• Combine meteorological observations and monitoring/deployment hardware data to optimize model initial conditions and forecasts.

• Construct an operational modeling pipeline for high-resolution WRF simulations using historical, forecast, and observational data.

• Assess AI and machine-learning weather models and emulators.

• Create cloud and high-performance computing workflows for model execution, data management, analysis, and visualization.

• Define technical priorities and relay scientific insights, limitations, and uncertainties to leadership and external research collaborators.

• Recruit, mentor, and guide atmospheric scientists, meteorologists, data scientists, and scientific software developers.

• Cultivate partnerships with universities, national laboratories, research institutions, and other scientific collaborators.

⛳️ Requirements

• A bachelor's degree or higher in atmospheric science, meteorology, physics, computer science, data science, or a related discipline.

• Extensive experience in atmospheric science, meteorology, weather forecasting, numerical weather prediction, or atmospheric research.

• Significant experience configuring, operating, and analyzing WRF.

• Familiarity with implementing WRFDA, DART, or similar data assimilation frameworks.

• Strong understanding of boundary layer meteorology, cloud microphysics, convective initiation, precipitation mechanisms, and mesoscale atmospheric dynamics.

• Proficient in interpreting radar, satellite, sounding, surface-station, and various meteorological observations.

• Experience with artificial intelligence and machine learning applications in weather modeling, weather emulators, or related atmospheric technologies.

• Proficient in running numerical weather prediction models in Linux, cloud computing, or high-performance computing settings.

• Extensive knowledge of meteorological datasets and formats such as NetCDF and GRIB.

• Strong programming skills in Python along with working knowledge of Fortran, C++, or other scientific computing languages.

• Experience in leading technical teams, establishing scientific priorities, and conveying complex results to both technical and non-technical audiences.

• Capability to handle competing priorities, meet deadlines, and perform effectively in a rapidly changing startup environment.

• Practical experience in deploying, operating, troubleshooting, or interpreting meteorological field equipment.

• Familiarity with lidar, weather radar, radiometers, radiosondes, disdrometers, ceilometers, or surface weather stations.

• Experience with field campaigns, environmental monitoring, or deployment operations in the Southwestern United States.

• Background working at a national laboratory, research university, government weather organization, or artificial intelligence weather enterprise.

🏝️ Benefits

• Significant equity.

• Remote work arrangement customized to the candidate's and team's needs.

• Option to be based in the San Francisco Bay Area, California, or New Mexico hubs.

• Frequent travel associated with the role.