Junior Geospatial Data Scientist (Pipeline & Algorithm Focus)

About the role

We are looking for a Junior Geospatial Data Scientist to build and maintain the processing pipelines and algorithms that turn our satellite's raw hyperspectral imagery into science-grade data products.

Key Responsibilities

• Build, test, and maintain scalable data processing pipelines for satellite imagery—from raw sensor data through calibrated, orthorectified, analysis-ready products.
• Write modular, well-documented Python code that runs reliably in cloud environments (AWS).
• Implement radiometric calibration, atmospheric correction, geometric orthorectification, and spectral resampling stages within automated workflows.
• Implement and optimize spectral analysis algorithms including classification, unmixing, regression, and retrieval methods for hyperspectral data.
• Translate mathematical and physical models (e.g., radiative transfer, Beer-Lambert law, spectral mixture analysis) into performant, validated code.
• Benchmark algorithm accuracy against ground truth and reference datasets.
• Manipulate complex raster data at scale using GDAL, Rasterio, Xarray, and related geospatial libraries.
• Work with high-dimensional spectral cubes—understanding data structures, coordinate systems, and metadata conventions (e.g., ENVI, GeoTIFF, NetCDF/HDF).
• Optimize data I/O, memory management, and compute for large imagery datasets.
• Apply your understanding of remote sensing physics (reflectance, radiance, atmospheric effects, sensor response functions) to ensure every pipeline stage is scientifically sound.
• Participate in calibration/validation efforts, comparing algorithm outputs against known references.
• Flag and investigate anomalies—understanding when results look wrong and diagnosing whether the issue is data, code, or physics.

Qualifications

• B.S. or M.S. in Applied Mathematics, Statistics, Physics, or a closely related quantitative field.
• Hands-on experience with hyperspectral or multispectral remote sensing data (spectral cubes, high-dimensional imagery).
• Strong Python proficiency with an engineering mindset—you write modular, testable, version-controlled code, not just scripts.
• Understanding of the math and physics behind remote sensing: reflectance, atmospheric correction, radiative transfer basics, spectral analysis.
• Experience with geospatial data tools: GDAL, Rasterio, Xarray, NumPy, SciPy.
• Comfort working with raster data formats and coordinate reference systems.

PREFERRED EXPERIENCE

• Building data pipelines in cloud environments (AWS S3, EC2, Lambda, Batch).
• Familiarity with atmospheric correction models (MODTRAN, 6S, FLAASH) or radiative transfer concepts.
• Exposure to ML frameworks (PyTorch, TensorFlow, scikit-learn) applied to geospatial data.
• Experience with software engineering practices: CI/CD, unit testing, code review, Git workflows.
• Coursework or research experience in remote sensing, imaging spectroscopy, or Earth observation.

Location

This role is based in San Francisco, CA, with onsite presence required. Ability to travel to San Francisco Bay Area or El Segundo offices as needed.

ITAR Requirements

To comply with U.S. export regulations, applicants must be one of the following: A U.S. citizen or national, A lawful permanent resident (green card holder), Eligible to obtain required authorizations from the U.S. Department of State.

Employee Offerings & Benefits

• Compensation: Competitive total package based on experience.
• Equity: Early-stage equity package so you share directly in Matter's growth and success.
• Health & Wellness: 100% employer-paid health, dental, and vision coverage.
• Growth: Opportunities to develop deep technical expertise and grow into senior scientist or engineering roles as we scale.