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Geospatial Analytics Jobs in California (NOW HIRING)

What you'll do As a Senior Analytics Engineer, you will own and extend our demand forecasting ... Develop and extend geospatial demand models using GIS tooling (H3, PostGIS, Kepler.gl, GeoPandas ...

Senior Analytics Engineer

Carlsbad, CA · On-site

$119K - $188K/yr

What you'll do As a Senior Analytics Engineer, you will own and extend our demand forecasting ... Develop and extend geospatial demand models using GIS tooling (H3, PostGIS, Kepler.gl, GeoPandas ...

Senior Analytics Engineer

Carlsbad, CA · On-site

$148K - $222K/yr

What you'll do As a Senior Analytics Engineer, you will own and extend our demand forecasting ... Develop and extend geospatial demand models using GIS tooling (H3, PostGIS, Kepler.gl, GeoPandas ...

Data Analyst

San Francisco, CA · On-site

$123K - $160K/yr

Previous experience working with geospatial analytics and spatial datasets. * Experience with large-scale time-series and mobility datasets (e.g., GTFS, GPS traces, transit logs). * Experience with ...

PhD and current Faculty/Professor status in Geospatial Analytics, Computer Science, Remote Sensing, or a related field. * Deep Domain Expertise: 12+ years of experience in remote sensing and ...

PhD and current Faculty/Professor status in Geospatial Analytics, Computer Science, Remote Sensing, or a related field. * Deep Domain Expertise: 12+ years of experience in remote sensing and ...

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Showing results 1-20

Geospatial Analytics information

See California salary details

$21.7K

$76.5K

$120.4K

How much do geospatial analytics jobs pay per year?

As of Jul 14, 2026, the average yearly pay for geospatial analytics 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 Analytics professional, and why are they important?

To thrive in Geospatial Analytics, you need strong spatial analysis skills, proficiency in geographic information systems (GIS), and a background in geography, computer science, or related fields. Familiarity with tools such as ArcGIS, QGIS, remote sensing software, and programming languages like Python or R is typically required, along with relevant certifications. Analytical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex spatial data and presenting findings to diverse stakeholders. These skills and qualifications are important for delivering actionable insights that inform decision-making across industries such as urban planning, environmental management, and logistics.

What is the difference between Geospatial Analytics vs GIS Analyst?

AspectGeospatial AnalyticsGIS Analyst
Required CredentialsBachelor's in Geography, GIS, or related field; proficiency in spatial analysis toolsBachelor's in Geography, GIS, or related field; GIS certifications often preferred
Work EnvironmentData analysis, modeling, and visualization in offices or remote settingsMap creation, data management, and spatial data editing in GIS software environments
Industry UsageUsed across industries like urban planning, environmental science, and transportation for data-driven decisionsPrimarily in government agencies, consulting firms, and environmental organizations for mapping and data management

While both roles involve spatial data, Geospatial Analytics focuses on analyzing and interpreting geographic data to derive insights, whereas a GIS Analyst primarily manages and creates geographic information systems and maps. Both roles often overlap but serve different core functions within the geospatial industry.

What are some common challenges faced by professionals in geospatial analytics, and how can they be addressed?

Professionals in geospatial analytics often encounter challenges such as managing large, complex datasets, ensuring data accuracy, and integrating information from diverse sources. To address these, it's important to develop strong skills in data cleaning, validation, and familiarity with various GIS and remote sensing tools. Collaboration with IT specialists and subject matter experts can also help streamline workflows and improve data integration. Staying updated on the latest industry software and best practices is key to overcoming technical hurdles and delivering actionable insights.

What is geospatial analytics?

Geospatial analytics is the process of gathering, analyzing, and interpreting data that is associated with specific locations on the Earth. It combines geographic information systems (GIS), satellite imagery, GPS data, and other spatial data sources to uncover patterns, relationships, and trends. Geospatial analytics is widely used in fields like urban planning, environmental science, disaster response, and business intelligence to make data-driven decisions based on location-specific insights.
What are popular job titles related to Geospatial Analytics jobs in California? For Geospatial Analytics jobs in California, the most frequently searched job titles are:
What cities in California are hiring for Geospatial Analytics jobs? Cities in California with the most Geospatial Analytics job openings:
Infographic showing various Geospatial Analytics job openings in California as of July 2026, with employment types broken down into 72% Full Time, 11% Part Time, and 17% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $76,480 per year, or $36.8 per hour.
Senior Analytics Engineer

Senior Analytics Engineer

Viasat, Inc.

Carlsbad, CA

$148K - $222K/yr

Full-time

Re-posted 21 days ago


Viasat rating

4.2

Company rating: 4.2 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

79th of 82 rated telecommunications companies


Job description

About us

One team. Global challenges. Infinite opportunities. At Viasat, we’re on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We’re looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team.


What you'll do

As a Senior Analytics Engineer, you will own and extend our demand forecasting platform, modeling satellite bandwidth requirements across Maritime, Aviation, Enterprise, and emerging Direct-to-Device (D2D) markets. You'll translate executive-level business questions into scalable data pipelines and geospatial models, driving iterative cycles of data interpretation and assumption refinement. You'll turn ambiguous forecasting challenges into production-quality analytical tools—and just as importantly, help senior leadership understand what the data is (and isn't) telling them.
Reporting to the Director, Commercial Business Analytics, you'll operate at the intersection of business strategy and data engineering—close enough to executive stakeholders to shape the why behind the models, and close enough to engineering to ensure your work can be productionized and scaled. Your forecasting outputs feed directly into capacity feasibility analyses run by engineering teams, making the handoff relationship critical.


The day-to-day
  • Partner directly with business unit executives and C-level stakeholders to translate strategic forecasting needs into data models, proactively surfacing insights and challenging assumptions
  • Own and evolve demand forecasting pipelines using Python, SQL, and modern orchestration tools (Dagster, dbt, BigQuery)
  • Develop and extend geospatial demand models using GIS tooling (H3, PostGIS, Kepler.gl, GeoPandas) to translate global market opportunity into demand projections for targeted geographies
  • Drive forecasting model expansion to new business units and services through configurable, testable code—often where no existing baseline exists
  • Independently validate model outputs, refine assumptions, and recommend adjustments to input parameters based on observed patterns and business feedback
  • Interpret and present forecasting outputs in business context to senior leadership—identifying where model results challenge assumptions, surfacing data quality risks, and advising on methodology changes
  • Evaluate and integrate 3rd-party industry data to assess total global vertical demand and model geographic distribution
  • Build data structures with engineering handoff in mind—balancing analytical flexibility with the conventions and standards that enable smooth transition to production systems
  • Document methodologies, assumptions, and maintain clear data lineage across all forecasting workstreams
  • Deliver regional and scenario-based demand projections that directly inform capacity planning decisions
  • Collaborate with engineering teams who consume forecasting outputs, ensuring data formats, assumptions, and methodologies are well-documented and aligned with downstream systems
  • Continuously evaluate existing forecasting processes and recommend improvements to enhance accuracy, scalability, and stakeholder confidence

What you'll need
  • Bachelor's degree in a quantitative field
  • 5–8 years of experience in analytics engineering, data engineering, or quantitative analysis
  • Demonstrated experience managing executive and cross-functional stakeholder relationships—translating complex analytical outputs into actionable business guidance
  • Hands-on GIS and geospatial analysis experience (e.g., H3, PostGIS, GeoPandas, Kepler.gl, or equivalent tooling)
  • Strong SQL and cloud data warehouse experience (BigQuery preferred)
  • Python proficiency with data engineering and analytical libraries (pandas, scipy, etc.)
  • Proven ability to structure ambiguous business problems into well-defined analytical frameworks
  • Experience building maintainable, scalable data pipelines with clear documentation and lineage
  • Strong written and verbal communication skills, including experience presenting to senior leadership
  • Comfort owning outcomes in fast-paced, evolving environments with minimal supervision

What will help you on the job
  • Master's degree or equivalent experience in a quantitative field
  • Experience transitioning analytical models into production infrastructure alongside engineering teams
  • Satellite or telecom industry experience
  • Hands-on experience with Dagster, Airflow, or dbt
  • Demand forecasting or capacity planning experience
  • Familiarity with spatial statistics, coverage modeling, or network planning tools

Salary range
$119,000.00 - $188,500.00 / annually.For specific work locations within San Jose, the San Francisco Bay area and New York City metropolitan area, the base pay range for this role is $148,500.00- $222,500.00/ annually
At Viasat, we consider many factors when it comes to compensation, including the scope of the position as well as your background and experience. Base pay may vary depending on job-related knowledge, skills, and experience. Additional cash or stock incentives may be provided as part of the compensation package, in addition to a range of medical, financial, and/or other benefits, dependent on the position offered. Learn more about Viasat's comprehensive benefit offerings that are focused on your holistic health and wellness at https://careers.viasat.com/benefits.
EEO Statement

Viasat is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, ancestry, physical or mental disability, medical condition, marital status, genetics, age, or veteran status or any other applicable legally protected status or characteristic. If you would like to request an accommodation on the basis of disability for completing this on-line application, please click here.

Qualifications:
  • Bachelor's degree in a quantitative field
  • 5–8 years of experience in analytics engineering, data engineering, or quantitative analysis
  • Demonstrated experience managing executive and cross-functional stakeholder relationships—translating complex analytical outputs into actionable business guidance
  • Hands-on GIS and geospatial analysis experience (e.g., H3, PostGIS, GeoPandas, Kepler.gl, or equivalent tooling)
  • Strong SQL and cloud data warehouse experience (BigQuery preferred)
  • Python proficiency with data engineering and analytical libraries (pandas, scipy, etc.)
  • Proven ability to structure ambiguous business problems into well-defined analytical frameworks
  • Experience building maintainable, scalable data pipelines with clear documentation and lineage
  • Strong written and verbal communication skills, including experience presenting to senior leadership
  • Comfort owning outcomes in fast-paced, evolving environments with minimal supervision
Education:UNAVAILABLEEmployment Type: FULL_TIME

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ViaSat logo

About ViaSat

Sourced by ZipRecruiter

At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate.

Industry

Telecommunications

Company size

5,001 - 10,000 Employees

Headquarters location

Carlsbad, CA, US

Year founded

1986