CAREERS

If you're a great meteorologist or electrical engineer, we want to hire you. Email resumes to jobs@windbornesystems.com.

WindBorne Systems aims to deliver better weather forecasts built on a proprietary balloon-based atmospheric sensing platform. Their system can travel a quarter of the way around the world in a single flight and navigate to capture data with the highest impact, filling the huge gaps in traditional measurements. The company is backed by Khosla Ventures, and the team, led by a Thiel fellow and a Hertz fellow, was recognized by Forbes 30 under 30. They developed their world-record-breaking technology through four years of Stanford research, and are working to build the next generation of weather prediction with the mission of helping humanity adapt to the growing threat of climate change -- and the extreme weather that comes along with it.

Data Assimilation Meteorologist

Email jobs@windbornesystems.com to apply

WindBorne is seeking an exceptional meteorologist skilled in data assimilation and numerical weather prediction (NWP) to assimilate our unique in-situ, atmospheric data source. As our first meteorological hire, you'll be building weather prediction with data no one else has access to. You will be on the forefront of weather, growing a team to help humanity adapt to climate change.

Responsibilities:

  • Assimilating data from targeted atmospheric observations into numerical weather models
  • Assessing and determining the best locations to target to maximize data impact
  • Growing and leading an exceptional team of meteorologists
  • Shaping a vision for how WindBorne develops a forward-thinking NWP system that highlights the value of these unique observation sources
Qualifications:
  • Deep experience with WRF or similar numerical weather models
  • Experience with a data assimilation system compatible with the WRF model, e.g. WRFDA, GSI, DART or JEDI
  • Experience analyzing and evaluating model performance
  • Strong meteorological intuition
  • Experience with ensemble forecast sensitivity analysis
Preferred:
  • Strong leadership abilities
  • Self-directed, creative, and scrappy
  • Experience with cloud-based infrastructure, eg AWS, Google Cloud
  • Experience with ensemble and 4DVAR data assimilation
  • Experience assimilating novel upper-air observations
  • Exposure to FORTRAN
  • Familiarity with Linux
  • Experience with MPAS