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Geospatial Data Scientist Jobs in California (NOW HIRING)

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Navy SEPASS Data Scientist

Monterey, CA

Koniag IT Systems, LLC is seeking a Lead Data Scientist to spearhead geospatial application programming efforts for our federal customers. The ideal candidate will bring extensive experience in data ...

Koniag, Inc.

Navy SEPASS Data Scientist

Monterey, CA · On-site

$195K - $205K/yr

Koniag IT Systems, LLC is seeking a Lead Data Scientist to spearhead geospatial application programming efforts for our federal customers. The ideal candidate will bring extensive experience in data ...

kgs

Navy SEPASS Data Scientist

Monterey, CA · On-site

Koniag IT Systems, LLC is seeking a Lead Data Scientist to spearhead geospatial application programming efforts for our federal customers. The ideal candidate will bring extensive experience in data ...

Hayden AI

Associate Data Scientist

San Francisco, CA · On-site

$120K - $156K/yr

Hayden AI seeks a Data Scientist to support a diverse set of stakeholders with Data and Analytics ... Previous experience working with geospatial analytics and spatial datasets. * Experience with large ...

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All JobsGeospatial Data Scientist JobsGeospatial Data Scientist Jobs in California

Geospatial Data Scientist information

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$37K

$121.1K

$193.9K

How much do geospatial data scientist jobs pay per year?

As of Jul 29, 2026, the average yearly pay for geospatial data scientist in California is $121,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

A geospatial data scientist can start or transition into the field at age 40, as data science values skills, experience, and continuous learning over age. Many professionals successfully switch careers or advance in data science later in life by acquiring relevant skills such as programming, statistics, and GIS tools, and obtaining certifications if needed.

What are the typical daily tasks of a Geospatial Data Scientist?

As a Geospatial Data Scientist, your daily tasks often involve collecting, cleaning, and analyzing spatial datasets using GIS tools and programming languages. You may be responsible for developing spatial models, visualizing geographic data through interactive maps, and generating reports to help guide strategic decisions. Collaboration with professionals from engineering, urban planning, or environmental science teams is common, requiring you to communicate complex analyses in a clear and actionable manner. Additionally, you might participate in project meetings to align your work with organizational goals and stakeholder needs. This dynamic role blends technical analysis with communication and teamwork, making each day varied and intellectually stimulating.

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

Geospatial Data Scientists require expertise in spatial analysis, statistics, and data modeling, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), programming languages like Python or R, and familiarity with spatial databases are often expected, while certifications in GIS can be advantageous. Strong problem-solving abilities, collaboration, and effective communication skills help professionals translate complex data into actionable insights and work well with diverse teams. Mastery of these skills ensures accurate geospatial analyses and supports informed, data-driven decision making in various industries.

Can data scientists make $300k?

Geospatial Data Scientists with extensive experience, advanced skills in GIS tools, programming, and machine learning can potentially earn $300,000 or more, especially in high-demand industries or senior roles. However, such salaries are typically achieved through seniority, specialized expertise, or leadership positions, and are not common for entry-level or mid-career roles.

Is GIS still in demand?

Geospatial Data Scientists and GIS professionals are in high demand due to the increasing reliance on spatial data across industries such as urban planning, environmental management, and logistics. Skills in GIS software, spatial analysis, and programming languages like Python or R enhance job prospects in this field, which continues to grow with advancements in technology and data integration.

What is a Geospatial Data Scientist job?

A Geospatial Data Scientist analyzes spatial and geographic data to extract insights, create predictive models, and support decision-making. They use tools like GIS, remote sensing, machine learning, and statistical analysis to process location-based data. Their work spans various industries, including urban planning, environmental monitoring, agriculture, and logistics. By leveraging spatial data, they help optimize operations, manage resources, and solve complex geographic problems.

What does a geospatial data scientist do?

A geospatial data scientist analyzes geographic data to identify patterns, trends, and insights using tools like GIS software, programming languages such as Python or R, and spatial databases. They develop models, visualize data on maps, and support decision-making in fields like urban planning, environmental management, and transportation.
What are the most commonly searched types of Geospatial Data Scientist jobs in California? The most popular types of Geospatial Data Scientist jobs in California are:
What are popular job titles related to Geospatial Data Scientist jobs in California? For Geospatial Data Scientist jobs in California, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Scientist jobs in California look for? The top searched job categories for Geospatial Data Scientist jobs in California are:
What cities in California are hiring for Geospatial Data Scientist jobs? Cities in California with the most Geospatial Data Scientist job openings:
Geospatial Data Scientist jobs near you
Infographic showing various Geospatial Data Scientist job openings in California as of July 2026, with employment types broken down into 79% Full Time, 15% Part Time, 3% Temporary, and 3% Contract. Highlights an 87% In-person, 3% Hybrid, and 10% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Data Scientist / Senior Data Scientist

Berkshire Hathaway Specialty Insurance

San Ramon, CA • On-site

Full-time

Re-posted 14 days ago

Job description

Job Summary:
Berkshire Hathaway Specialty Insurance (BHSI) is a strategic and trusted insurance partner providing a broad range of commercial insurance coverages. They are seeking a Data Scientist / Senior Data Scientist to join the Catastrophe Engineering and Analytics team, responsible for applying data science techniques to assess risk and develop models for various natural and man-made perils.
Responsibilities:
• Evaluate and develop insights into large and diverse data sets from claims, hazard models, structural analysis, geospatial sources, and various other public/proprietary datasets.
• Develop and maintain expertise in advanced data science, machine learning, and artificial intelligence techniques, and their application to understanding risk.
• Work with domain experts across teams and perils to enhance our use of available data.
• Propose and execute innovative solutions to insurance problems that directly impact BHSI underwriting decisions.
Qualifications:
Required:
• Ph.D. or M.S. in data science, civil engineering, atmospheric science, actuarial science, computer science, mathematics, or a related field
• Advanced knowledge of probability theory, statistics, and machine learning methods is required
• Experience applying advanced statistical techniques and machine learning to large data sets, especially in areas of structural performance, natural catastrophe hazard, building exposure data, geospatial data, or insurance claims data
• Familiarity with large language models (LLMs), retrieval-augmented generation (RAG), and their application in data-driven workflows is a plus
• Strong written and verbal communication skills
• Comfort working within git-based version-control environments
• Highly motivated, detail oriented, and team player
Preferred:
• 3-6 years of industry experience is preferred and required for the Senior Data Scientist level role
• Practical experience in insurance, catastrophe model development, cyber and casualty risk modeling, and/or exposure data collection is preferred
• Strong programming skills in Python (preferred), R, and SQL
• Experience and understanding of relational and non-relational databases preferred
• Experience with Databricks or other cloud-based data and analytics platforms preferred
Company:
Berkshire Hathaway Specialty Insurance is a company providing risk solutions and claims care. Founded in 2013, the company is headquartered in Boston, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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