ZipRecruiter

Log In

1

Geospatial Data Science Jobs in California (NOW HIRING)

Pano

Geospatial Data Engineer

San Francisco, CA · On-site

$111K - $144K/yr

This role works closely with geospatial data analysts, data scientists, and cross-functional partners in Sales, Operations, Product, and Engineering to ensure that spatial data is reliable, scalable ...

Shipt

Data Scientist

San Francisco, CA · On-site +1

Data Science, Geospatial Data, Geospatial Modeling, Python (Programming Language) Bachelor's Degree or equivalent experience| Required Work Arrangement Shipt considers candidates located near a Shipt ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Green Diamond Resource Company

Geospatial Analyst

Korbel, CA · Hybrid

$71.05K - $106.57K/yr

... data analysis, interpretation, and writing scientific papers and technical reports. * Develop and maintain database management systems and geospatial data pipelines; serve as on-site resource for GIS ...

GREEN DIAMOND RESOURCE COMPANY

Geospatial Analyst

Korbel, CA · On-site

$71.05K - $106.57K/yr

... data analysis, interpretation, and writing scientific papers and technical reports. * Develop and maintain database management systems and geospatial data pipelines; serve as on-site resource for GIS ...

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.
Geospatial Data Engineer

Geospatial Data Engineer

Pano

San Francisco, CA • On-site

$111K - $144K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago

Job description

Help us tackle the growing wildfire crisis with the latest advancements in AI and IoT
Who we are
The problem: Every minute matters in fire response. As climate change amplifies the intensity of wildfires-with longer fire seasons, dryer fuels, and faster winds-new ignitions spread faster and put more communities at risk. Today, most wildfires are detected by bystanders and reported via 911, meaning it can take hours to detect a fire, verify its exact location and size, and dispatch first responders. Fire authorities need a faster way to detect, confirm, and pinpoint fires so that they can quickly respond-preventing small flare-ups from becoming devastating infernos.
About Pano: We are a 175+ person growth-stage hybrid-remote start-up, headquartered in San Francisco. We are the leader in early wildfire detection and intelligence, helping fire professionals respond to fires faster and more safely-with the right equipment, timely information, and enhanced coordination-so that they can stop a new ignition before it grows. Pano AI combines advanced hardware, software, and artificial intelligence into an easy-to-use, web-based platform. Leveraging a network of ultra-high-definition, 360-degree cameras atop high vantage points, as well as satellite and other data feeds, Pano AI produces a real-time picture of threats in a geographic region and delivers immediate, actionable intelligence.
Pano AI has been recognized by Fast Company as one of the Top 10 Most Innovative AI Companies in 2023, and as one of the Top 50 Most Innovative Companies of 2026-ranking #1 in the Sustainability category. The company was also named to TIME's list of the 100 Most Influential Companies of 2025 and identified by MIT Technology Review as one of the top 15 climate tech companies to watch in 2024. Pano AI has been featured in leading publications, including The Wall Street Journal, Bloomberg, and CNBC.
The company serves dozens of government and enterprise customers across 16 U.S. states, five Australian states, and British Columbia, Canada, and currently monitors more than 50 million acres of land worldwide. It has raised $89 million in venture capital from investors including Giant Ventures, Liberty Mutual Ventures, Tokio Marine Future Fund, Congruent Ventures, Initialized Capital, Salesforce Ventures, and T-Mobile Ventures. Learn more at https://www.pano.ai/.
The Role
As a Geospatial Data Engineer on the Geospatial Analytics team, you will design, build, and maintain the data infrastructure that powers Pano AI's geospatial analytics workflows-from ingestion pipelines and spatial databases to automated processing systems and internal tooling. This role works closely with geospatial data analysts, data scientists, and cross-functional partners in Sales, Operations, Product, and Engineering to ensure that spatial data is reliable, scalable, and readily accessible. An ideal candidate brings 2-4 years of experience in data or software engineering, solid command of Python and SQL, and hands-on familiarity with geospatial data formats and spatial databases. You will contribute to the full data lifecycle, writing clean and well-tested code, participating in code reviews, and helping establish engineering standards on a growing team.
What you'll do
  • Design, build, and maintain scalable data pipelines that ingest, transform, and load geospatial datasets to support efficient and scalable geospatial analytics
  • Develop and optimize PostGIS and PostgreSQL database schemas to support geospatial analytics, viewshed computations, and site selection workflows
  • Write and maintain Python-based automation scripts and geospatial processing tools, following software engineering best practices including code reviews, pull requests, and version control with Git/GitHub
  • Collaborate with geospatial data analysts and scientists to understand data requirements and translate them into reliable, well-documented engineering solutions
  • Monitor and maintain data quality, pipeline reliability, and system performance for production geospatial data products
  • Support integration of geospatial data infrastructure with internal dashboards, APIs, and product engineering systems
  • Support analytics workflows as needed
  • Contribute to special projects and cross-functional initiatives as the team's data infrastructure needs evolve

What you'll bring
  • Bachelor's degree in Computer Science, Engineering, Geography, Statistics, Math, or a related field
  • 2-4 years of experience in data engineering, software engineering, or a closely related role
  • Proficiency in Python, including experience writing modular, tested, and maintainable code using geospatial Python libraries such as GeoPandas, Shapely, Rasterio, or GDAL
  • Solid SQL skills and hands-on experience with PostgreSQL and PostGIS for querying and managing spatial data
  • Fluency with Git/GitHub workflows, including branching strategies, pull requests, and code reviews
  • Working knowledge of geospatial data formats (GeoJSON, GeoTIFF, Shapefile, etc.) and coordinate reference systems
  • Experience building or maintaining ETL or data pipeline workflows in a production environment
  • Strong communication skills and ability to work collaboratively across technical and non-technical stakeholders
  • Experience with ArcGIS Pro or QGIS highly preferred

Nice to have
  • Experience with cloud-based geospatial platforms or data warehouses (e.g., BigQuery, Snowflake, AWS, or GCP)
  • Experience with Salesforce integrations
  • Experience with ArcGIS Online and ArcGIS Enterprise
  • Experience with workflow orchestration tools such as Temporal, Airflow, Prefect, or similar

Final compensation for full-time employees is determined by a variety of factors, including job-related qualifications, education, experience, skills, knowledge, and geographic location. In addition to base salary, full-time roles are eligible for stock options. Our benefits package also includes comprehensive medical, dental, and vision coverage, a matching 401(k) plan, and flexible paid time off.

Apply