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Volunteer Insurance Data Analytics Jobs in Oregon

Preferred Experience with Databricks, Thoughtspot, , and other data lake / warehouse and analytics ... Additional coverages available - Pet Insurance, Critical Illness Insurance, and Voluntary Life & AD ...

Senior Data Analyst - Financial Analytics

OR ยท On-site +1

$132K - $173K/yr

This role will leverage best practices in data modeling, visualization, and analytics to deliver ... We offer a full benefits package, including medical, dental, vision, life insurance, disability ...

Leverage data and information to fundamentally alter outcomes for the business * Help evaluate and ... Insurance- Basic, Voluntary, and AD amp;D โ€ข Healthcare- Medical, Dental, Vision, and MDLive โ€ข ...

Sr Data Analyst

OR ยท Remote

$82K - $154K/yr

BECU Cares volunteer time off + donation match To join our dynamic team, we require candidates to ... Lead Analytics Initiatives: You'lllead end-to-end data analysis projects supporting divisional ...

Sr. Data Steward

OR ยท On-site +1

$75K - $100K/yr

Proficiency with SQL and analyzing large datasets. * Proven experience defining, motivating, and ... Benefits & Perks * Paid "UA Give Back" Volunteer Days: Work alongside your team to support ...

Our team of analysts, scientists, engineers, and strategists hail from diverse backgrounds yet ... health insurance plan * 401K matching * Unlimited vacation * Paid sick, personal, and volunteer ...

Enterprise Performance Analytics Engineer

OR ยท Remote

$80K - $110K/yr

Transform data into well-documented, tested, and trusted datasets for analysis and reporting ... insurance plan options * Health Savings Account and Flexible Spending Accounts * Bi-weekly HSA ...

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Volunteer Insurance Data Analytics information

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 Oregon? The most popular types of Insurance Data Analytics jobs in Oregon are:
What job categories do people searching Volunteer Insurance Data Analytics jobs in Oregon look for? The top searched job categories for Volunteer Insurance Data Analytics jobs in Oregon are:
What cities in Oregon are hiring for Volunteer Insurance Data Analytics jobs? Cities in Oregon with the most Volunteer Insurance Data Analytics job openings:

Contractor

Posted 12 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.