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Insurance Data Analyst Jobs (NOW HIRING)

BizTek People

Insurance Data Analyst

Portland, OR · On-site

Insurance Data Analyst 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 ...

1 point system

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 ...

Georgia IT Inc

Insurance Data Analyst

Manhattan, NY · On-site

Data Analyst With Insurance Domain Location: NYC, NY Duration: Long Term Skills Required: * Detailed knowledge of commercial insurance underwriting process in both for property and liability lines

Orion180

Senior Insurance Data Analyst

Irving, TX · On-site

$82K - $104K/yr

JOIN OUR TEAM AS A SENIOR INSURANCE DATA ANALYST!! We believe analytics isn't a back-office function. It's not a reporting layer bolted onto the business after the real decisions get made. It's the ...

E-Solutions

Reporting Data Analyst

Lenexa, KS · On-site

Reporting Data Analyst Onsite locations: Alpharetta, GA; Charlotte, NC; Chicago, IL; Conshohocken ... Translate insurance business concepts into accurate data logic, metrics, and dimensional ...

E-Solutions

Reporting Data Analyst

Morristown, NJ · On-site

Reporting Data Analyst Onsite locations: Alpharetta, GA; Charlotte, NC; Chicago, IL; Conshohocken ... Translate insurance business concepts into accurate data logic, metrics, and dimensional ...

E-Solutions

Reporting Data Analyst

Alpharetta, GA · On-site

Reporting Data Analyst Onsite locations: Alpharetta, GA; Charlotte, NC; Chicago, IL; Conshohocken ... Translate insurance business concepts into accurate data logic, metrics, and dimensional ...

E-Solutions

Reporting Data Analyst

Garden City, NY · On-site

Reporting Data Analyst Onsite locations: Alpharetta, GA; Charlotte, NC; Chicago, IL; Conshohocken ... Translate insurance business concepts into accurate data logic, metrics, and dimensional ...

E-Solutions

Reporting Data Analyst

Charlotte, NC · On-site

Reporting Data Analyst Onsite locations: Alpharetta, GA; Charlotte, NC; Chicago, IL; Conshohocken ... Translate insurance business concepts into accurate data logic, metrics, and dimensional ...

E-Solutions

Reporting Data Analyst

Mount Juliet, TN · On-site

Reporting Data Analyst Onsite locations: Alpharetta, GA; Charlotte, NC; Chicago, IL; Conshohocken ... Translate insurance business concepts into accurate data logic, metrics, and dimensional ...

E-Solutions

Reporting Data Analyst

Chicago, IL · On-site

ROLE SUMMARY The Reporting Data Analyst partners with business groups across the Property & Casualty (P&C) insurance domain to define and deliver reporting and data extracts requirements. This role ...

FEDRUS GLOBAL LLC

Reporting Data Analyst

Alpharetta, GA · On-site

8+ years as a hands-on IT Reporting Data Analyst 4+ years in reporting/data analysis within Property & Casualty insurance (reinsurance experience a plus) 3+ years hands-on experience with reporting ...

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Insurance Data Analyst information

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$34K

$82.6K

$136K

How much do insurance data analyst jobs pay per year?

As of Jul 8, 2026, the average yearly pay for insurance data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

How much does an insurance analyst make?

An insurance data analyst typically earns between $60,000 and $85,000 annually, depending on experience, location, and certifications. Entry-level positions may start lower, while experienced analysts with advanced skills or specialized knowledge can earn higher salaries. They often work with data analysis tools like Excel, SQL, and statistical software in an office environment.

What is the difference between Insurance Data Analyst vs Actuary?

AspectInsurance Data AnalystActuary
Required CredentialsBachelor's degree in statistics, data science, or related field; often certifications like CAP or CPCUBachelor's degree in mathematics, statistics, or actuarial science; professional actuarial exams and credentials (e.g., ASA, FSA)
Work EnvironmentData analysis teams within insurance companies, focusing on data modeling and reportingActuarial departments, focusing on risk assessment, pricing, and reserving
Employer & Industry UsageInsurance companies, brokers, and consulting firmsInsurance companies, consulting firms, government agencies

While both roles involve working with insurance data, Insurance Data Analysts focus on data collection, analysis, and reporting, whereas Actuaries specialize in risk modeling and financial forecasting using advanced mathematics and actuarial exams. The roles often collaborate but serve different strategic functions within insurance organizations.

Do insurance companies need a data analyst?

Insurance companies rely on data analysts to interpret large datasets, assess risk, and support decision-making processes. Data analysts use tools like SQL and Excel, and often require industry knowledge and analytical skills to improve underwriting, claims management, and pricing strategies.

What are the key skills and qualifications needed to thrive as an Insurance Data Analyst, and why are they important?

To thrive as an Insurance Data Analyst, you need strong analytical skills, proficiency in statistics, and a background in mathematics, finance, or a related field, often supported by a relevant degree. Familiarity with data analysis tools such as SQL, Excel, Python, and data visualization platforms, as well as knowledge of insurance-specific databases and certifications like CPCU or AIDA, is highly valued. Attention to detail, problem-solving, and effective communication are crucial soft skills for interpreting complex data and presenting insights to stakeholders. These skills ensure accurate risk assessment, data-driven decision-making, and effective support of business objectives in the insurance industry.

How does an Insurance Data Analyst typically collaborate with underwriters and actuaries?

Insurance Data Analysts frequently work alongside underwriters and actuaries to provide data-driven insights that inform risk assessment and pricing decisions. Analysts gather, clean, and interpret large sets of policyholder and claims data, then present actionable findings through reports or dashboards. Regular meetings and joint projects ensure that underwriters and actuaries have the most accurate, up-to-date information to make decisions, and that data models align closely with business needs. Strong communication and teamwork skills are essential for success in this collaborative environment.

What does an Insurance Data Analyst do?

An Insurance Data Analyst is responsible for collecting, processing, and analyzing data related to insurance policies, claims, customer behavior, and market trends. They use statistical tools and software to identify patterns, assess risks, and provide actionable insights that help insurance companies make informed decisions. Their work supports pricing strategies, fraud detection, customer retention, and overall business performance. Insurance Data Analysts often collaborate with underwriters, actuaries, and business managers to optimize processes and improve profitability.

What does a data analyst do in insurance?

An insurance data analyst examines large datasets to identify trends, assess risk, and support decision-making for insurance policies and claims. They use tools like Excel, SQL, and data visualization software to interpret data and improve underwriting, pricing, and fraud detection processes.

Is 40 too late for data science?

For an Insurance Data Analyst, age is not a barrier to entering data science. Many professionals successfully transition into data roles later in their careers by developing relevant skills such as programming, statistics, and data visualization, often through online courses or certifications. Experience in insurance or related fields can also be valuable in this career path.
More about Insurance Data Analyst jobs
What cities are hiring for Insurance Data Analyst jobs? Cities with the most Insurance Data Analyst job openings:
What states have the most Insurance Data Analyst jobs? States with the most job openings for Insurance Data Analyst jobs include:
What job categories do people searching Insurance Data Analyst jobs look for? The top searched job categories for Insurance Data Analyst jobs are:
Insurance Data Analyst jobs near you
Infographic showing various Insurance Data Analyst job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 86% Full Time, 6% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Insurance Data Analyst

Insurance Data Analyst

BizTek People

Portland, OR • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Insurance Data Analyst

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. This role involves consolidating information from claims, policies, exposures, and historical loss records; performing data quality checks; identifying inconsistencies or gaps; and preparing structured datasets aligned with Riskonnect's data mapping and upload requirements. The contractor will leverage advanced Excel skills—including complex formulas, data cleansing techniques, pivot tables, and data validation tools—to efficiently transform and audit large datasets prior to migration. They will collaborate closely with internal stakeholders and the implementation team to ensure accurate data 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 a fast-moving implementation environment are essential.

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