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Remote Geospatial Data Scientist Jobs in Riverside, CA

We have an exciting opportunity for a Data Scientist within our data product space. This individual ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Mine and ...

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

We have an exciting opportunity for a Data Scientist within our data product space. This individual ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Mine and ...

This role focuses on translating field-collected geospatial survey data into accurate AutoCAD ... Occasional coordination with remote field teams supporting airport infrastructure projects ...

AutoCAD Draftsman

Ontario, CA · On-site +1

$34.62 - $40/hr

This role focuses on translating field-collected geospatial survey data into accurate AutoCAD ... remote field teams supporting airport infrastructure projects Compensation Hourly Rate Range: $34 ...

The Manager Data Science is responsible for architecting, building, and deploying production-grade ... This is a remote position. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Design, build, train, and ...

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Remote Geospatial Data Scientist information

See Riverside, CA salary details

$39.1K

$128K

$205K

How much do remote geospatial data scientist jobs pay per year?

As of Sep 13, 2026, the average yearly pay for remote geospatial data scientist in Riverside, CA is $128,049.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,800.00 and $141,900.00 per year, depending on experience, location, and employer.

What is a remote geospatial data scientist?

A Remote Geospatial Data Scientist is a professional who analyzes and interprets spatial data, such as maps, satellite imagery, and GPS data, to solve problems or provide insights, all while working from a location outside of a traditional office. They use statistical, mathematical, and programming skills to process large geospatial datasets and often collaborate with teams virtually. Their work can support a variety of industries, including environmental monitoring, urban planning, and logistics, by providing actionable geographic insights. Remote geospatial data scientists commonly use tools like GIS software, Python, and machine learning frameworks. Communication and collaboration tools are also essential for effective remote work.

What are the key skills and qualifications needed to thrive as a remote geospatial data scientist?

To thrive as a Remote Geospatial Data Scientist, you need a strong background in spatial analysis, statistics, and programming, typically supported by a degree in geography, computer science, or a related field. Experience with GIS software (such as ArcGIS or QGIS), remote sensing tools, and programming languages like Python or R is essential, along with familiarity with cloud-based data platforms. Strong problem-solving, self-motivation, and effective communication skills are vital for collaborating remotely and turning complex geospatial data into actionable insights. These skills enable professionals to efficiently interpret and analyze spatial data, deliver valuable solutions, and work effectively within distributed teams.

How do remote geospatial data scientists typically collaborate with multidisciplinary teams across different time zones?

Remote Geospatial Data Scientists often work with professionals in fields like environmental science, urban planning, and software engineering, many of whom may be distributed globally. Effective collaboration relies on clear communication, regular virtual meetings, and the use of shared platforms for data, code, and project management. Flexible scheduling and asynchronous communication tools are key to coordinating across time zones, ensuring that all team members can contribute to project milestones efficiently. Building strong documentation and leveraging collaborative GIS and data platforms further help streamline workflows and maintain project momentum in a remote environment.

What is the difference between Remote Geospatial Data Scientist vs Remote GIS Analyst?

AspectRemote Geospatial Data ScientistRemote GIS Analyst
Required CredentialsBachelor's/Master's in GIS, Geography, Data Science; experience with spatial analysisBachelor's in GIS, Geography, or related field; proficiency in GIS software
Work EnvironmentData analysis, modeling, programming, and spatial data interpretationMapping, data management, spatial data visualization
Employer & Industry UsageTech companies, environmental agencies, urban planningGovernment agencies, utilities, environmental firms
Common Search & ComparisonFocuses on data science and modelingFocuses on mapping and spatial data management

The Remote Geospatial Data Scientist primarily works on advanced spatial data analysis, modeling, and programming to extract insights from geospatial data. In contrast, the Remote GIS Analyst focuses on mapping, data management, and spatial visualization. Both roles require GIS knowledge but differ in their core responsibilities and skill sets.

What job categories do people searching Remote Geospatial Data Scientist jobs in Riverside, CA look for?

The top searched job categories for Remote Geospatial Data Scientist jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Remote Geospatial Data Scientist jobs?

Cities near Riverside, CA with the most Remote Geospatial Data Scientist job openings:

Infographic showing various Remote Geospatial Data Scientist job openings in Riverside, CA as of September 2026, with employment types broken down into 67% Full Time, 15% Part Time, and 18% Contract. Highlights an 100% Remote job distribution, with an average salary of $128,049 per year, or $61.6 per hour.

Data Scientist II

Irvine, CA • On-site, Remote

Corvel
Insurance Services • 1 - 5K employees

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


CorVel rating

7.9

Company rating: 7.9 out of 10

Based on 51 frontline employees who took The Breakroom Quiz


Job description

We have an exciting opportunity for a Data Scientist within our data product space. This individual will be focused on designing, building, and deploying machine learning models and data products that support our enterprise initiatives. This role focuses on developing scalable, production ready solutions by translating complex business problems into data-driven approaches and model-based outputs.

Working closely with product managers, engineering teams, and business stakeholders, this position contributes to the development of data products from concept through deployment, ensuring solutions are reliable, performant, and aligned with real world use cases. The role includes hands on model development, feature engineering, and integration into production systems within cloud environments.

The ideal candidate has experience building and operationalizing machine learning models and is comfortable working with modern AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), where applicable. Experience with platforms such as Azure, AWS, or similar ecosystems is strongly preferred.

Success in this role requires strong technical expertise, problem-solving skills, and the ability to deliver high-quality solutions within a structured development environment. This role focuses on building and deployment of production data products and is not limited to exploratory analysis or reporting.

This position is open to remote or hybrid.

ESSENTIAL FUNCTIONS & RESPONSIBILITIES:

  • Mine and analyze data from internal databases to drive optimization and improvement of product development and business strategies
  • Creating new, experimental frameworks to collect data
  • Building tools to automate data collection
  • Develop custom data models and algorithms to apply to data sets
  • Design, build, train, and deploy machine learning models and data products for enterprise use
  • Translate business and operational needs into scalable data science solutions and modeling approaches
  • Perform feature engineering, data preparation, and exploratory analysis to support model development
  • Develop and evaluate models using appropriate techniques (e.g., classification, regression, NLP, optimization)
  • Contribute to the design of data products, including model outputs, APIs, and integration into downstream systems
  • Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate
  • Collaborate with engineering teams to integrate models into production environments using APIs, pipelines, and cloud services
  • Support deployment and lifecycle management of models within Azure Machine Learning, AWS, or similar platforms
  • Perform model validation, testing, and documentation to ensure quality and reproducibility
  • Contribute to technical design discussions and provide input on architecture and implementation strategies
  • Work within the full software development lifecycle (SDLC), including version control, testing, and release processes
  • Communicate model behavior, assumptions, and results clearly to technical and non-technical stakeholders
  • Develop A/B testing framework and test model quality
  • Passion for technology and emerging AI/ML trends
  • Additional duties as assigned

KNOWLEDGE & SKILLS:

  • Strong problem-solving skills with an emphasis on product development.
  • Strong foundation in machine learning, statistical modeling, and data science techniques
  • Experience building and deploying machine learning models in production environments
  • Familiarity with modern AI approaches, including:
    • Natural language processing (NLP)
    • Large language models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • Feature engineering and model evaluation techniques
  • Experience working with cloud platforms such as Azure, AWS, or similar ecosystems
  • Familiarity with data pipelines, APIs, and integration patterns
  • Proficiency in programming languages such as Python and database management including SQL
  • Strong problem-solving skills with the ability to structure complex problems into analytical solutions
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), their real-world advantages/drawbacks and experience with applications
  • Excellent presentation and written/verbal communication skills

EDUCATION & EXPERIENCE:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master’s preferred
  • 2–5+ years of experience in data science, machine learning, or related roles
  • Experience developing and deploying machine learning models in production environments
  • Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar
  • Exposure to AI platforms such as Azure OpenAI, AWS Bedrock, or similar technologies preferred
  • Experience working within enterprise software environments and SDLC practices preferred

PAY RANGE:

CorVel uses a market based approach to pay and our salary ranges may vary depending on your location.  Pay rates are established taking into account the following factors:  federal, state, and local minimum wage requirements, the geographic location differential, job-related skills, experience, qualifications, internal employee equity, and market conditions.  Our ranges may be modified at any time.

For leveled roles (I, II, III, Senior, Lead, etc.) new hires may be slotted into a different level, either up or down, based on assessment during interview process taking into consideration experience, qualifications, and overall fit for the role.  The level may impact the salary range and these adjustments would be clarified during the offer process.

Pay Range:  $82,574 – $127,490

A list of our benefit offerings can be found on our CorVel website: CorVel Careers | Opportunities in Risk Management

In general, our opportunities will be posted for up to 1 year from date of posting, or until we have selected candidate(s) to fulfill the opening, whichever comes first.

About CorVel

CorVel, a certified Great Place to Work® Company, is a national provider of industry-leading risk management solutions for the workers’ compensation, auto, health and disability management industries.   CorVel was founded in 1987 and has been publicly traded on the NASDAQ stock exchange since 1991. Our continual investment in human capital and technology enable us to deliver the most innovative and integrated solutions to our clients.  We are a stable and growing company with a strong, supportive culture and plenty of career advancement opportunities.  Over 4,000 people working across the United States embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).

A comprehensive benefits package is available for full-time regular employees and includes Medical (HDHP) w/Pharmacy, Dental, Vision, Long Term Disability, Health Savings Account, Flexible Spending Account Options, Life Insurance, Accident Insurance, Critical Illness Insurance, Pre-paid Legal Insurance, Parking and Transit FSA accounts, 401K, ROTH 401K, and paid time off.

CorVel is an Equal Opportunity Employer, drug free workplace, and complies with ADA regulations as applicable.

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