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Volunteer Insurance Data Analytics Jobs in Portland, OR

This role will focus on integrating and analyzing data from multiple systems to identify trends ... Pet Insurance nLIGHT is subject to US Export Control regulations. To qualify for this position, you ...

IS Data Warehouse Architect III

Portland, OR · On-site

$126.72 - $154.88/hr

... L specifications, data analysis, system design and architecture, standards and policy ... CareOregon offers medical, dental, vision, life, AD&D, and disability insurance, as well as health ...

This role will focus on integrating and analyzing data from multiple systems to identify trends ... Pet Insurance nLIGHT is subject to US Export Control regulations. To qualify for this position, you ...

This role will focus on integrating and analyzing data from multiple systems to identify trends ... Pet Insurance nLIGHT is subject to US Export Control regulations. To qualify for this position, you ...

Design, develop, and maintain enterpriselevel data models to support analytics, reporting, and ... From health, dental, and vision coverage to life and disability insurance, PTO, and a 401(k) with ...

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Showing results 1-20

Volunteer Insurance Data Analytics information

See Portland, OR salary details

$26

$58

$100

How much do volunteer insurance data analytics jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for volunteer insurance data analytics in Portland, OR is $58.06, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $65.77 per hour, depending on experience, location, and employer.

What is the difference between Volunteer Insurance Data Analytics vs Insurance Data Analyst?

AspectVolunteer Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsRelevant certifications, data analysis skills, insurance knowledgeDegree in statistics, data science, or related field; certifications preferred
Work EnvironmentNon-profit, volunteer-based, flexible hoursCorporate insurance companies, structured office settings
Employer & Industry UsageNon-profit organizations, insurance charitiesInsurance firms, financial institutions
Common Search & ComparisonVolunteer Insurance Data Analytics vs Insurance Data Analyst

Volunteer Insurance Data Analytics focuses on analyzing insurance data within volunteer or non-profit contexts, often with flexible or part-time roles. Insurance Data Analysts work in corporate settings, handling large datasets to inform business decisions. Both roles require similar analytical skills and insurance knowledge but differ mainly in work environment and employment type.

What are the most commonly searched types of Insurance Data Analytics jobs in Portland, OR? The most popular types of Insurance Data Analytics jobs in Portland, OR are:
What are popular job titles related to Volunteer Insurance Data Analytics jobs in Portland, OR? For Volunteer Insurance Data Analytics jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Volunteer Insurance Data Analytics jobs in Portland, OR look for? The top searched job categories for Volunteer Insurance Data Analytics jobs in Portland, OR are:
What cities near Portland, OR are hiring for Volunteer Insurance Data Analytics jobs? Cities near Portland, OR with the most Volunteer Insurance Data Analytics job openings:

Contractor

Re-posted 28 days ago


Job description


Title: Insurance Data Analyst
Duration: 2 Months
Location: Portland, OR
Job Description
The Insurance Data Analyst contractor will play a key role in supporting our transition to Riskonnect by gathering, validating, and analyzing insurance related data required for system configuration and ongoing reporting.
Requirements
Responsibilities
  • This role involvesconsolidating information from claims, policies, exposures, and historicalloss records; performing data quality checks; identifying inconsistenciesor gaps; and preparing structured datasets aligned with Riskonnect's datamapping and upload requirements.
  • The contractor will leverageadvanced Excel skills-including complex formulas, data cleansingtechniques, pivot tables, and data validation tools-to efficientlytransform and audit large datasets prior to migration.
  • They will collaborate closelywith internal stakeholders and the implementation team to ensure accuratedata migration, support user acceptance testing with analytical insights,and document data processes to enable smooth adoption of the new platform.
  • Clear communication,meticulous attention to detail, and the ability to work independently in afast-moving implementation environment are essential.