Scientific Programmer


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.

As a Scientific Programmer at Spire, you will be an integral part of an extremely agile team focused on operating and developing products from a growing number of Earth observation satellites. You will work across the various disciplines of satellite remote sensing and data analysis, retrieval algorithm and product development, and measurement calibration and validation. You will work with the world’s premier nanosatellite Earth observations team to develop products from our unique payloads. You will develop the remote sensing algorithms and codes to turn GNSS and other measurements into valuable products for a wide variety of global customers, and these products will lead the field in Earth observations from commercial CubeSats. You will have the responsibility to ensure that we deliver high-quality, low-latency Earth remote sensing products and the freedom to pursue novel, high-impact applications. And instead of your ideas and efforts sitting on a shelf or hidden in an academic journal, you will see and experience them actually working in space within months of joining Spire.

Responsibilities of your role:

  • Develops and programs integrated software algorithms to structure, analyze and leverage data in product and systems applications. 
  • Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms. 
  • In both theoretical development environments and specific product design, implementation, and improvement environments, uses current programming language and technologies to translate algorithms and technical specifications into production code. 
  • Can work with large-scale cloud computing frameworks, data analysis systems, and modeling environments.
  • Completes programming and implements efficiencies, performs testing and debugging. 
  • Authors documentation and procedures for internal and external customers

Basic requirements: 

  • Applicants must have either an MSc or Ph.D. degree in STEM or associated qualification.
  • Demonstrated experience programming for geoscience applications, models, data assimilations systems, or remote sensing data analysis.
  • Demonstrated proficiency in Python.
  • Exceptionally well-organized, with the ability to go as deep as needed in any project to identify and resolve problems.
  • Adaptability to develop new ideas and the ability to push the envelope to deliver unique applications in Earth observations and their applications.
  • Excellent written and verbal communication skills.
  • Demonstrated working experience in geoscience programming and/or applying machine learning techniques and advanced data science techniques to problems.
  • Quantitative background in Statistics, Computer Science, Math or other technical fields.
  • Expertise with common analysis tools available in Python

Preferred qualifications

  • Demonstrated experience coding for geoscience production environments.
  • Application of machine learning techniques to geoscience data.
  • Knowledge and research experience in satellite remote sensing. 
  • Understanding of research and techniques in processing geoscience data. 
  • Experience developing potentially scalable systems in an industry or research environment.
  • Proficiency in C or C++ programming.
  • Strong Linux and open-source background.
  • Experience deploying in cloud-based environments, e.g., AWS.

Spire is Global and our success draws upon the diverse viewpoints, skills and experiences of our employees. We are proud to be an equal opportunity employer and are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status.