FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Head of Atmospheric Research
Roadrunner Venture Studios. Lead the atmospheric science function and connect scientific validation with operational deployment .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in atmospheric science and meteorology, with a strong focus on numerical weather prediction, data assimilation, and high-performance computing. Capable of leading technical teams, developing operational modeling chains, and effectively communicating complex scientific findings.
Highest-signal resume keywords
Atmospheric Science ExpertiseWeather Research And Forecasting (WRF) ModelingData Assimilation Systems (WRFDA, DART)Artificial Intelligence And Machine Learning ApplicationsNumerical Weather Prediction In Linux Environments
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Numerical Weather PredictionData AssimilationPython ProgrammingFortran ProgrammingC++ ProgrammingMeteorological Data AnalysisHigh-Performance ComputingCloud Computing WorkflowsBoundary Layer MeteorologyWeather Radar Interpretation
Soft Skills
LeadershipCommunicationMentoringTeam CollaborationTime Management
Tools & Technologies
WRFDADARTNetCDFGRIBDoppler Lidar SystemsWeather RadarRadiosondesCeilometersDisdrometersSurface Weather Stations
Industry Keywords
Atmospheric ResearchMeteorologyWeather PredictionField CampaignsEnvironmental Monitoring
Tech Stack
Tools & technologiesCloudDartLinuxPythonC++
About the role
Key responsibilities & impact- Lead the atmospheric science function and connect scientific validation with operational deployment
- Set scientific strategy for evaluating atmospheric conditions, selecting deployment windows, interpreting results, and improving operating criteria
- Integrate forecasts, historical datasets, soundings, radar, satellite imagery, surface observations, and field-sensor data into scientific assessments
- Review data before, during, and after deployments; compare predicted and observed conditions and communicate conclusions and uncertainty
- Work with science, software, and field teams to improve observation methods, data quality, operational prediction, and post-deployment analysis
- Lead the Weather Research and Forecasting (WRF) modeling program for deployment planning, atmospheric prediction, scenario analysis, and post-deployment review
- Architect WRF data assimilation using WRFDA, DART, or similar frameworks
- Build an operational modeling chain for high-resolution WRF simulations
- Evaluate AI and machine learning weather models and emulators
- Develop cloud and high-performance computing workflows for model execution, data management, analysis, and visualization
- Set technical priorities and communicate scientific findings, limitations, and uncertainty to leadership and research partners
- Recruit, mentor, and lead atmospheric scientists, meteorologists, data scientists, and scientific software engineers
- Build relationships with universities, national laboratories, research institutions, and scientific partners
Requirements
What you’ll need- Bachelor's degree or higher in atmospheric science, meteorology, physics, computer science, data science, or a related field
- Broad experience in atmospheric science, meteorology, weather prediction, numerical weather prediction, or atmospheric research
- Extensive experience configuring, running, and analyzing WRF
- Experience implementing WRFDA, DART, or similar data assimilation systems
- Strong knowledge of boundary layer meteorology, cloud microphysics, convective initiation, precipitation processes, and mesoscale atmospheric dynamics
- Experience interpreting forecasts and observations from radar, satellite, soundings, surface stations, or other meteorological systems
- Prior experience with artificial intelligence and machine learning weather modeling, weather emulators, or related atmospheric applications
- Experience running numerical weather prediction models in Linux, cloud computing, or high performance computing environments
- Deep experience with meteorological datasets and formats such as NetCDF and GRIB
- Strong Python skills and working knowledge of Fortran, C++, or similar scientific computing languages
- Experience leading technical teams, setting scientific priorities, and communicating complex results to technical and nontechnical audiences
- Ability to manage competing priorities, meet deadlines, and work effectively in a fast-changing startup environment
- Hands-on experience deploying, operating, troubleshooting, or interpreting data from meteorological field equipment
- Experience with Doppler lidar systems, weather radar, radiometers, radiosondes, disdrometers, ceilometers, or surface weather stations
- Experience with field campaigns, environmental monitoring, or deployment operations in the Southwest United States
- Experience at a national laboratory, research university, government weather organization, or artificial intelligence weather company
Benefits
Comp & perks- Significant equity
- Balance between in-person and remote work can be tailored to the candidate and team needs
- Frequent travel required