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Freelance Insurance Data Analytics Jobs (NOW HIRING)

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Insurance Data Analyst

New York, NY · Remote

Required Qualifications * 5+ years of experience working with insurance bordereaux (BDX) reporting, premium reporting, or insurance data analysis. * Strong understanding of MGA, Program, P&C, or ...

Risk Strategies

Senior Insurance Data Analyst

$84K - $115K/yr

The Senior Insurance Data Analyst plays a strategic role in advancing Oxford-wide analytics ... Lead enterprise data analytics initiatives: develop and execute analytics strategies that support ...

Novella

Insurance Data Scientist

New York, NY · On-site

Hands-on experience with insurance loss data, loss development, exposure analysis, and rate adequacy. * Experience building models that have been deployed in production and used to make real ...

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Freelance Insurance Data Analytics information

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$153K

$178.7K

$202K

How much do freelance insurance data analytics jobs pay per year?

As of Aug 23, 2026, the average yearly pay for freelance insurance data analytics in the United States is $178,749.00, according to ZipRecruiter salary data. Most workers in this role earn between $165,500.00 and $191,500.00 per year, depending on experience, location, and employer.

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

AspectFreelance Insurance Data AnalyticsInsurance Data Analyst
CredentialsOften self-taught or with certifications; formal degrees preferredBachelor's or higher in data analysis, statistics, or related fields
Work EnvironmentRemote, flexible projects for multiple clientsTypically in-house or remote within insurance companies or agencies
Employer & Industry UsageFreelance platforms, consulting firms, insurance companiesInsurance firms, underwriting companies, brokers

Freelance Insurance Data Analytics involves independent work on various projects, offering flexibility and diverse experience. In contrast, an Insurance Data Analyst usually works within an organization, focusing on ongoing data analysis to support business decisions. Both roles require strong analytical skills, but their work settings and client interactions differ significantly.

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What are the most commonly searched types of Insurance Data Analytics jobs?

The most popular types of Insurance Data Analytics jobs are:

What states have the most Freelance Insurance Data Analytics jobs?

States with the most job openings for Freelance Insurance Data Analytics jobs include:

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Freelance Insurance Data Analytics jobs near you
Infographic showing various Freelance Insurance Data Analytics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $178,749 per year, or $85.9 per hour.

Insurance Data Analyst

BizTek People, Inc. | APA International Placement Consultants

Portland, OR • On-site

Contractor

Re-posted 10 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.

Apply