How to apply for Senior Applied Scientist, Geospatial

About Muon Space

Muon Space is a mission-driven startup building a constellation of small satellites to deliver high-fidelity Earth observation data for climate monitoring and environmental intelligence. Their focus on first-principles science and end-to-end ownership makes them a unique place for scientists who want to see their work directly impact climate action.

About the role

As a Senior Applied Scientist, you will bridge the gap between raw satellite imagery and actionable insights by conducting feasibility studies, developing prototype products, and translating customer needs into technical requirements. Your work will directly shape new mission concepts and enable novel climate applications from space-based remote sensing.

A typical day

A typical day might start with reviewing satellite data downlink and running a quick quality check on spectral calibration. You'll then dive into a literature survey for a new mission concept, followed by a cross-functional meeting with engineers to discuss sensor requirements. In the afternoon, you might prototype an algorithm for detecting a specific atmospheric feature, then write up findings for a customer discovery call.

Who Muon Space is looking for

• A scientist with a deep physics-based understanding of EO/IR remote sensing, who can derive sensor performance from first principles rather than relying solely on black-box tools.
• Experienced in pixel-level analysis of multispectral/hyperspectral imagery, with a strong grasp of spectral unmixing, atmospheric correction, and calibration/validation techniques.
• Proficient in Python (NumPy, SciPy, GDAL, rasterio) and comfortable with large geospatial datasets; experience with cloud platforms (AWS, GCP) is a plus.
• A collaborative researcher who enjoys both independent deep dives into the literature and working closely with engineers and customers to define requirements.

Tips for this application

• Highlight any experience with early-stage mission concept development or trade studies—Muon values candidates who can work from scratch, not just apply existing algorithms.
• Showcase a portfolio of geospatial analysis projects (e.g., GitHub repo, published papers, or open-source contributions) that demonstrate your ability to go from raw pixels to insights.
• In your cover letter, explicitly connect your past work to climate applications (e.g., methane detection, vegetation health, disaster monitoring) to show alignment with Muon's mission.
• Tailor your resume to emphasize first-principles thinking: include examples where you derived sensor specifications, modeled radiative transfer, or validated physical models against real data.
• If you have experience with satellite tasking, data fusion, or working with EO/IR sensor manufacturers, make sure it stands out—these are directly relevant to the role.

What to cover in your cover letter

['Your ability to think from first principles: describe a time you derived a solution from physics fundamentals rather than using off-the-shelf tools.', 'Your experience with end-to-end product development: from customer need identification through prototype to validation.', "Your passion for climate action and how your geospatial expertise can contribute to Muon's mission of revolutionizing climate monitoring.", 'Your comfort with ambiguity and early-stage projects: Muon is a startup, and this role involves shaping new mission concepts.']

Research before applying

• Read Muon Space's blog and press releases to understand their satellite platforms (e.g., Muon Halo) and data products.
• Study their approach to thermal infrared imaging and how it differs from traditional EO satellites—this is a key differentiator.
• Look into their partnerships and customer segments (e.g., government, agriculture, energy) to understand the types of problems they solve.
• Familiarize yourself with the latest trends in small satellite constellations for climate monitoring (e.g., GHG emissions, wildfire detection).

Likely interview topics

Based on the job description, expect questions about:

• Describe how you would perform a feasibility study for a new Earth observation mission concept (e.g., detecting methane leaks from space).
• Walk through the steps to calibrate and validate a multispectral imager using ground truth data.
• How do you handle atmospheric correction for a spaceborne sensor? What are the key challenges?
• Given a trade study between spatial resolution, spectral bands, and revisit time, how would you prioritize for a specific climate application?
• Explain a time you had to translate a vague customer need into a clear technical requirement and prototype a solution.

Common mistakes to avoid

• Don't focus solely on machine learning or deep learning—Muon emphasizes physics-based understanding, so balance AI skills with first-principles science.
• Avoid generic remote sensing experience without demonstrating deep knowledge of sensor physics, calibration, and trade-offs.
• Don't neglect the 'applied' aspect: they want scientists who build products, not just publish papers. Show tangible outputs.