1

Spatial Data Science Jobs in California (NOW HIRING)

Data Analyst

San Francisco, CA · On-site

$123K - $160K/yr

Master's or PhD in Data Science, Transportation, or a related field. * Previous experience working with geospatial analytics and spatial datasets. * Experience with large-scale time-series and ...

MS or PhD in Statistics, Applied Mathematics, Computer Science, or other quantitative fields * 2+ years of experience with geospatial data (ex. GPS traces, spatial indexing systems, or routing ...

... spatial audio, world-class workouts and meditations, super fun games and more! The Apple Media Products Data Science & Analytics organization is passionate about developing discerning insights and ...

... data mapping, spatial analysis, and geographic information systems (GIS). In this role, you will ... Bachelor's degree in Geography, Environmental Science, Computer Science, or related field.

... data mapping, spatial analysis, and geographic information systems (GIS). In this role, you will ... Bachelor's degree in Geography, Environmental Science, Computer Science, or related field.

... data mapping, spatial analysis, and geographic information systems (GIS). In this role, you will ... Bachelor's degree in Geography, Environmental Science, Computer Science, or related field.

System Engineer- Enterprise Data Engineer

Redlands, CA · On-site

$107K - $133K/yr

... such as spatial data types, coordinate systems, and spatial indexing • Ability to clearly ... science, mathematics, GIS, or related STEM field Preferred : • Experience with ArcGIS Enterprise ...

next page

Showing results 1-20

Spatial Data Science information

See California salary details

$43.9K

$128K

$175.2K

How much do spatial data science jobs pay per year?

As of Jun 13, 2026, the average yearly pay for spatial data science in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What is the highest paying GIS job?

The highest paying GIS jobs are often senior roles such as GIS Director, Geospatial Data Scientist, or GIS Manager, with salaries exceeding $100,000 annually. These positions typically require advanced skills in spatial analysis, programming, and leadership, and may involve working with tools like ArcGIS, Python, or SQL.

What is spatial data science?

Spatial data science is a field that combines data science techniques with geographic information systems (GIS) to analyze and interpret spatial or location-based data. It involves collecting, processing, and visualizing data that has a geographic or spatial component, such as maps, satellite images, or GPS coordinates. Spatial data scientists use methods from statistics, machine learning, and computer science to solve problems related to urban planning, environmental monitoring, transportation, and more. The insights gained from spatial data science help organizations make better decisions based on the relationships and patterns found in geographic data.

Is GIS hard to get a job in?

Getting a job in GIS or spatial data science can be competitive, but having strong skills in GIS software like ArcGIS or QGIS, programming languages such as Python or R, and a solid understanding of spatial analysis can improve employability. Relevant certifications and a portfolio of projects also enhance job prospects in this field.

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

To thrive as a Spatial Data Scientist, you need a strong background in statistics, geospatial analysis, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases (like PostGIS), and relevant certifications (e.g., Esri Technical Certification) is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication are vital soft skills to interpret spatial data and convey insights to stakeholders. These competencies are crucial for extracting actionable insights from complex geospatial datasets and supporting informed decision-making.

Is 40 too late for data science?

Age is generally not a barrier to entering a data science or spatial data science career, as skills and experience are more important. Many professionals successfully transition into data science later in life by acquiring relevant skills such as programming, statistics, and data visualization, often through online courses or certifications. Employers value diverse experiences, and continuous learning can help you stay competitive regardless of age.

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

AspectSpatial Data ScienceGeospatial Analyst
Required CredentialsDegree in GIS, Geography, Data Science, or related fields; often includes certifications in GIS or data analysisDegree in Geography, GIS, or related fields; certifications in GIS software are common
Work EnvironmentData analysis, modeling, and programming; often in tech or research settingsMapping, data visualization, and GIS software use; typically in government, environmental, or urban planning agencies
Employer & Industry UsageTech companies, research institutions, urban planning, environmental agenciesGovernment agencies, environmental consultancies, urban planning firms

Spatial Data Science focuses on analyzing spatial data using advanced data science techniques, programming, and modeling. In contrast, Geospatial Analysts primarily work with GIS software to create maps and visualize spatial data. While both roles require GIS knowledge, Spatial Data Scientists often have stronger programming and statistical skills, working on complex data analysis projects, whereas Geospatial Analysts focus more on mapping and data visualization tasks.

Is GIS a high demand job?

GIS (Geographic Information Systems) professionals, including those in spatial data science, are in high demand across industries such as urban planning, environmental management, and transportation. The growing use of spatial analysis, remote sensing, and GIS software like ArcGIS and QGIS contributes to strong job prospects and competitive salaries in this field.

What are some typical challenges spatial data scientists face when integrating geospatial data from multiple sources?

Spatial data scientists often encounter challenges like inconsistencies in data formats, varying coordinate reference systems, and differences in spatial resolution when integrating geospatial data from multiple sources. Addressing these requires familiarity with data transformation tools and a strong understanding of spatial data standards. Additionally, ensuring data quality and managing large datasets can be complex, so attention to detail and effective use of GIS software are crucial for successful integration.
What cities in California are hiring for Spatial Data Science jobs? Cities in California with the most Spatial Data Science job openings:
Infographic showing various Spatial Data Science job openings in California as of June 2026, with employment types broken down into 13% Internship, 49% Full Time, 25% Temporary, and 13% Contract. Highlights an 87% In-person, and 13% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.
Senior Marketing Data Scientist, Media Subscriptions

Senior Marketing Data Scientist, Media Subscriptions

Apple

Culver City, CA • On-site

Full-time

Posted 12 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps, award-winning shows and movies, immersive music in spatial audio, world-class workouts and meditations, super fun games and more...The Apple Media Products Data Science & Analytics organization is passionate about developing discerning insights and machine learning solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy.
We are currently seeking an experienced data scientist who is passionate about motivating change at the intersection of data and marketing. As a Marketing Data Scientist for Apple Services, you will help drive growth in media services and evolve our marketing programs through attribution, causal inference, A/B testing, and LTV prediction modeling. Your work will directly influence Services strategy for driving engagement and revenue growth. As a key member of our diverse and dynamic organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to customer privacy that will frequently require innovative approaches. You'll work collaboratively with partners across Business, Marketing, Product, and Engineering daily to deliver material customer and business value.
5+ years of experience extracting business insights from large datasets, specifically employing programming languages like Python and SQLDemonstrated ability in a Data Scientist or Data Analyst role, preferably for a digital media, MarTech, digital subscription business, or technology businessExcellent communication and presentation skills with meticulous attention to detail with the ability to communicate effectively between marketing, business and analytics teamsExperience with standard marketing data science analysis to include experimental design, linear regression, clustering, survival, and quasi-causal analysis, with solid experience measuring both paid and non-paid campaignsCurious business mindset with an ability to condense complex concepts and analysis into clear and concise takeaways that drive actionBachelors degree in Computer Science, Economics, Engineering, Mathematics, Data Science, Statistics or equivalent professional experience
Experience in and/or passion for the media and entertainment industryExperience analyzing the performance of subscription businesses and familiarity with subscription lifecycle metricsSkilled at measuring advertising value through causal inference techniquesAdvanced degree in a related field preferred

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976