ZipRecruiter

Log In

1

Geospatial Data Science Jobs in California (NOW HIRING)

Koniag, Inc.

Navy SEPASS Data Scientist

Monterey, CA · On-site

$195K - $205K/yr

The ideal candidate will bring extensive experience in data science, machine learning, and geospatial software development. This role requires someone who can lead complex analytical projects, mentor ...

kgs

Navy SEPASS Data Scientist

Monterey, CA

The ideal candidate will bring extensive experience in data science, machine learning, and geospatial software development. This role requires someone who can lead complex analytical projects, mentor ...

kgs

Navy SEPASS Data Scientist

Monterey, CA

The ideal candidate will bring extensive experience in data science, machine learning, and geospatial software development. This role requires someone who can lead complex analytical projects, mentor ...

LLNL

Energy Resilience Data Scientist

Livermore, CA · On-site

... science (NumPy, SciPy, Matplotlib).Demonstrated experience performing geospatial analytics in ... PhDin data science, applied statistics, computer science, engineering or a related field, or the ...

LLNL

Energy Resilience Data Scientist

Livermore, CA · On-site

... science (NumPy, SciPy, Matplotlib). Demonstrated experience performing geospatial analytics in Python, using GeoPandas or equivalent geospatial tools and libraries. * Comprehensive knowledge and ...

LLNL

Energy Resilience Data Scientist

Livermore, CA

... science (NumPy, SciPy, Matplotlib). Demonstrated experience performing geospatial analytics in Python, using GeoPandas or equivalent geospatial tools and libraries. * Comprehensive knowledge and ...

Cinder LLC

AV Safety Data Engineer

Foster City, CA · On-site

$90/hr

Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related ... Experience with geospatial data analysis * Experience with business intelligence tools such as ...

next page

Showing results 1-20

People also search for

All JobsGeospatial Data Science JobsGeospatial Data Science Jobs in California

Geospatial Data Science information

See California salary details

$21.7K

$76.5K

$120.4K

How much do geospatial data science jobs pay per year?

As of May 30, 2026, the average yearly pay for geospatial data science in California is $76,480.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,800.00 and $79,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Geospatial Data Scientist, and why are they important?

To thrive as a Geospatial Data Scientist, you need a solid background in statistics, spatial analysis, and programming, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases, and coding languages like Python or R is essential, and certifications in GIS can be advantageous. Strong problem-solving skills, attention to detail, and effective communication help translate complex spatial data into actionable insights for diverse stakeholders. These skills ensure accurate data analysis, innovative solutions, and impactful decision-making in fields reliant on geographic information.

How does a Geospatial Data Scientist typically collaborate with other departments or teams within an organization?

Geospatial Data Scientists often work closely with professionals from diverse departments such as urban planning, environmental science, IT, and business analytics. Collaboration usually involves sharing spatial insights, integrating geospatial data with other datasets, and contributing to interdisciplinary projects that require spatial analysis or mapping. Effective communication is crucial, as you'll translate complex geospatial findings into actionable recommendations for non-technical stakeholders. This cross-functional teamwork not only broadens your understanding of organizational goals but also enhances the impact and visibility of geospatial analyses.

What is geospatial data science?

Geospatial data science is an interdisciplinary field that focuses on analyzing and interpreting data that has a geographic or spatial component. It combines techniques from data science, statistics, and geographic information systems (GIS) to extract insights, identify patterns, and solve problems related to location-based data. Professionals in this field work with mapping, remote sensing, spatial analysis, and visualization tools to support decision-making in areas like urban planning, environmental monitoring, and logistics.

What is the difference between Geospatial Data Science vs GIS Analyst?

AspectGeospatial Data ScienceGIS Analyst
Required CredentialsDegree in Data Science, Geography, or related; often includes programming skillsDegree in Geography, GIS, or related; GIS certifications common
Work EnvironmentData analysis, modeling, programming, often in tech or research settingsMapping, spatial data management, using GIS software in various industries
Employer & Industry UsageTech companies, research institutions, government agencies focusing on spatial data analysisUrban planning, environmental agencies, utilities, and government agencies

While both roles work with spatial data, Geospatial Data Science emphasizes data analysis, modeling, and programming skills to extract insights from geospatial data. GIS Analysts focus more on mapping, data management, and using GIS software for spatial analysis. The roles often overlap but differ mainly in technical focus and application areas.

What are the most commonly searched types of Geospatial Data Science jobs in California? The most popular types of Geospatial Data Science jobs in California are:
What are popular job titles related to Geospatial Data Science jobs in California? For Geospatial Data Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Science jobs in California look for? The top searched job categories for Geospatial Data Science jobs in California are:
What cities in California are hiring for Geospatial Data Science jobs? Cities in California with the most Geospatial Data Science job openings:
Geospatial Data Science jobs near you
Infographic showing various Geospatial Data Science job openings in California as of May 2026, with employment types broken down into 5% As Needed, and 95% Full Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $76,480 per year, or $36.8 per hour.

Senior Geospatial Scientist

Matter Intelligence

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision

Posted 27 days ago

Job description

About Matter Intelligence
Welcome to Matter, where we are building the future of vision AI: pairing a world-first sensor that sees molecular chemistry, temperature, and 3D shape with a Large World Model that will be the most powerful intelligence engine for our physical world. This system doesn't just see what something looks like; it understands everything from a single pixel. We call this Superintelligent Vision.
You'll join a team that has delivered technologies to Mars for NASA/JPL, co-founded and led infrastructure for OpenAI, designed cutting-edge sensors for U.S. Defense, and invented core algorithms for spectral and 3D imaging. We've come together to build the next infrastructure for vision and intelligence in the physical world.
About the Role
We are seeking a Senior Geospatial Scientist to lead the development of algorithms and data pipelines that transform our ultraspectral imagery into actionable intelligence. This role sits at the intersection of remote sensing science, machine learning, and scalable cloud infrastructure-turning raw hyperspectral data into validated, production-ready data products.
You will design and implement physics-informed ML algorithms, build robust AWS-based processing pipelines, and ensure the scientific validity of every output-from sensor physics through final data products. Your work will directly enable Matter's mission to deliver transformative Earth-observation capability across industries.
Key Responsibilities
Algorithm Development
  • Design and implement Machine Learning (ML) and physics-informed algorithms for hyperspectral data analysis.
  • Develop spectral unmixing, classification, and regression models for diverse geospatial applications.
  • Translate domain science (agriculture, mineralogy, ecology, aquatics) into validated algorithmic approaches.
  • Leverage modern AI tools to accelerate code generation and problem-solving.

Pipeline Architecture
  • Build and maintain scalable data processing pipelines on AWS to handle large-scale geospatial datasets.
  • Architect systems for radiometric correction, atmospheric compensation, and geometric orthorectification.
  • Optimize pipelines for throughput, latency, and cost across petabyte-scale imagery.

Scientific Validation
  • Evaluate the efficacy and accuracy of data products with rigorous statistical validation.
  • Maintain deep scientific understanding of all pipeline elements-from sensor physics to final output.
  • Design and execute calibration/validation campaigns using ground truth and reference data.

Team Collaboration
  • Partner with the Image Processing team to refine algorithms and support high-volume data processing.
  • Work closely with sensor engineers, systems engineers, and mission operations to ensure end-to-end data quality.
  • Contribute to technical proposals, publications, and customer engagements.

What Success Looks Like
  • Production-ready algorithms delivering validated data products at scale.
  • Robust, well-documented pipelines handling diverse hyperspectral workflows.
  • Clear scientific validation demonstrating data product accuracy and reliability.
  • Cross-functional partnerships enabling seamless sensor-to-insight workflows.

Qualifications
Required
  • PhD in a Geospatial-related field with 2+ years of experience, OR Master's degree with 5+ years of experience.
  • Proven experience processing hyperspectral reflectance data and developing associated algorithms.
  • Experience applying geospatial analysis in at least two distinct domains (e.g., Agriculture, Mineralogy, Ecology, Cryosphere, Aquatics).
  • Strong proficiency in Scientific Computing (Python, NumPy, SciPy, xarray, rasterio, GDAL).
  • Experience with AWS cloud infrastructure (S3, EC2, Lambda, Batch, or similar).
  • Deep understanding of math/statistics and geospatial fundamentals (coordinate projections, remote sensing instrumentation, GIS theory).
  • Demonstrated high proficiency in using LLMs (ChatGPT, Gemini, Claude) for coding productivity and workflow optimization.

Preferred
  • Experience with spaceborne or airborne remote sensing missions.
  • Familiarity with atmospheric correction models (e.g., MODTRAN, 6S, FLAASH).
  • Experience with deep learning frameworks (PyTorch, TensorFlow) for geospatial applications.
  • Track record of publications or patents in remote sensing or geospatial science.
  • Experience in rapid development or startup environments.

Location
This role is based in San Francisco, CA, with onsite presence required (temporary remote flexibility may be considered). 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
At Matter, we believe in rewarding high performance and providing the support you need to thrive. Our compensation and benefits package includes:
  • 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 expand into leadership, strategic accounts, or cross-functional roles as we scale.

Who You Are
You are a scientist-engineer who bridges deep domain expertise with production-grade software. You think rigorously about data quality, communicate clearly with both technical and non-technical stakeholders, and thrive in environments where your work directly shapes products that matter.

Apply