Senior Remote Sensing Data Scientist (Cal/Val)

Join Muon Space, a company dedicated to building advanced infrared imaging missions for global wildfire detection, weather monitoring, and environmental monitoring. As a Senior Remote Sensing Data Scientist, you will play a crucial role in developing the on-orbit data calibration system and translating calibration algorithms into production pipelines. You will work closely with calibration scientists, IR instrument engineers, and product teams to ensure the scientific quality and radiometric integrity of Muon's IR data products. This is a remote position with a focus on software engineering and data science.

• Contribuer à la conception, à la construction et à l'exploitation de pipelines de calibration et de traitement d'images de qualité production pour les missions FireSat et SBEM de Muon.
• Traduire les algorithmes de calibration en code de production robuste, bien testé, et posséder la stratégie de test à travers les suites de tests unitaires, d'intégration et de régression.
• Collaborer avec les scientifiques de calibration, les ingénieurs d'instrumentation IR et les équipes de produits pour construire et maintenir des services de calibration opérationnels et garantir la qualité scientifique des produits de données IR de Muon.

• Exceptional Python software engineering skills, including modern packaging, testing frameworks (e.g., pytest), version control, code review, and CI/CD workflows
• PhD with 3+ years, MS with 6+ years, or BS with 8+ years of industry experience
• 4+ years of experience calibrating imaging instruments
• Ability to thrive in a fast-paced start up environment
• Solid grounding in statistics, applied mathematics, and enough instrument physics to reason about calibration algorithms, radiometric error budgets, and their diagnostics — and to design meaningful automated quality visualizations on top of them
• Demonstrated experience taking scientific or numerical algorithms — for example calibration, image-processing, or signal-processing algorithms — from prototype to hardened, maintainable production code, including designing unit and integration test suites and quantitative validation against reference data
• Ability to work with a distributed, interdisciplinary team (scientists, engineers, data support)
• Proven track record shipping and operating production data or analytics pipelines for scientific data — including monitoring, logging, alerting, and automated testing — ideally in a remote sensing, calibration, or other measurement-instrument context
• Hands-on experience with complex data from new imaging instruments
• This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency
• We encourage you to apply, even if you don't check all the boxes, and we look forward to reviewing your application! In addition, if you need a reasonable accommodation as part of your application for employment or interviews with us, please let us know
• Deep knowledge of the science of remote sensing and radiometric calibration, including SI-traceability and uncertainty analysis
• Experience with mid-wave infrared instruments and MWIR data processing, and hands-on experience calibrating on-orbit imaging instruments — radiometric, spectral, and geometric
• Experience with detector characterization (dark current, non-uniformity, linearity, noise, MTF, or PRNU/DSNU), calibration campaign design (blackbodies, integrating spheres, on-board calibrators, deep convective clouds, lunar or vicarious calibration sites), and/or geospatial data processing
• Familiarity with common geospatial data tooling and formats (e.g. XArray, COG, NetCDF), and with building automated visualization or dashboarding tools for scientific data (e.g., Plotly, Panel, Streamlit, Grafana)
• Familiarity with containerization and workflow orchestration (Docker, Kubernetes, Airflow, Prefect, Argo, or similar)
• Experience with cloud-native systems and infrastructure-as-code (AWS preferred)
• Experience working with large TB-sized datasets, and domain expertise in geospatial analytics