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Data Assimilation Scientist - NWP

Spire — Boulder
Data Assimilation Scientist - NWP - image

Spire Global is a space-to-cloud analytics company that owns and operates the largest multi-purpose constellation of satellites. Its proprietary data and algorithms provide the most advanced maritime, aviation, and weather tracking in the world. In addition to its constellation, Spire’s data infrastructure includes a global ground station network and 24/7 operations that provide real-time global coverage of every point on Earth.

 Spire Global is seeking a Data Assimilation Scientist to contribute to the development of advanced Data Assimilation (DA) methods; they will utilize data from Spire’s GNSS-RO/GNSS-R satellite constellation and other sources to create world-class Numerical Weather Prediction (NWP) forecasts. This is an exciting opportunity for motivated scientists to make a difference through advancing DA techniques and assimilating unprecedented numbers of Radio Occultation (GNSS-RO) and Reflectometry (GNSS-R) observations. The successful candidate will join the Data Assimilation Group in Boulder, Colorado; they will work on issues of international significance with top-level scientists at Spire, as well as scientists from around the world.


The successful candidate will work with Spire DA, weather forecast, and software engineering teams to implement and evaluate cutting-edge DA methods. They will assimilate space, air, and ground based observations into a global NWP model. The assimilation of Spire’s own GNSS data into this model represents a unique opportunity; never before have so many GNSS observations been assimilated into an NWP model. Responsibilities will include the following:

  • Proposing and implementing innovative approaches to DA, data processing and quality control.
  • Implementing cutting-edge capabilities for assimilating GNSS-RO, GNSS-R and other satellite data into the NWP model.
  • Developing and implementing methodologies for estimating forecast sensitivity to observations.
  • Combining data assimilation and machine learning methods.
  • Working with the Spire software engineering team to define most effective software solutions.
  • Collaborating with the JCSDA/JEDI community on unified DA and observation operator development.
  • Presenting research findings at scientific conferences or workshops and publishing scientific papers.


  • Applicants must have either a MS or PhD degree in Meteorology, Atmospheric Science, Mathematics, or equivalent working experience in DA methods.
  • Working experience with cutting-edge DA methods such as 4D-Var or hybrid ensemble-variational methods is strongly preferred; experience with ensemble Kalman filter (EnKF), 3D-Var, and other techniques is also of interest.
  • Working experience with DA systems involving community NWP models such as FV3, MPAS and GFS.
  • Working experience with JCSDA/JEDI DA tools and forward operators.
  • Working knowledge of Fortran, Python, Linux scripting and version control (e.g., Git, SVN, Bitbucket).
  • Working experience with meteorological data formats (e.g., NetCDF, BUFR, and GRIB) and software tools (e.g., ESMF) is desirable.
  • Knowledge of optimal control theory and minimization methods is desirable.
  • Demonstration of enthusiasm and ability to work in a development team that never stops improving DA methods and results.



Space Program Engineering11

Weather Engineering6

Space Program Science & Research1

Weather Science & Research1


BMSS (Sales and Marketing)12

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