Filling the gaps between
Reach Us
Reach Us
Terms &
Spirepedia is a collection of miniature articles about topics mentioned throughout the Spire website.
Reach us

Mathematical Modeler

Spire — Boulder, San Francisco
Mathematical Modeler - image

Spire Global is a 150 person space data company founded in 2012 that designs and operates one of the largest satellite constellations in the world, and several analytics applications. The company owns the entire stack from custom hardware to customer APIs. We are seeking a skilled and motivated computer modeler.

Qualified applicants have strong math skills, are knowledgeable in the area of optimization techniques, and can demonstrate experience designing and modifying mathematical models of natural and designed systems.  


Among other things, you will be working on the following projects:  

1) schedule optimization system for our space program. The schedule tasks instruments and software defined networking systems for over 100 assets moving at 17000 miles per hour. Our links are asymmetric and intermittent. Power and thermal and mutual exclusion of various modes need to be considered. The value of our constellation data firehose needs to be maximized. This is determined by the importance of the geographic area, how often it’s observed, observation quality, observation volume, and latency of data downlink. The success of this mission is subject to the performance of our MIP based schedule optimization system.  

2) constellation performance modeling. By modeling the performance of our constellation in terms of various reception metrics, you will help Spire understand our overall effectiveness and also inform the schedule optimization for special applications. This modeling would incorporate 4D parameterization globally, including hindcast assessment as well as performance forecast.

Responsibilities of your role:

  • You will be the infrastructure team’s go to expert on mathematical modeling and statistics.
  • As part of this job you will drive technical vision and execution for the formulation of the constellation optimization problem.


  • Graduate degree in applied mathematics, operations research / engineering, computer science, or related field  
  • Strong familiarity of optimization techniques, especially mixed-integer linear / nonlinear programming
  • Creation of models, writing sophisticated routines in at least one programming language is required.  
  • Facility with Python, as well as CPLEX / Gurobi, or similar optimization packages is required.
  • GIS and data visualization techniques
  • Ability to meet deadlines and work as a part of a diverse distributed team