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Entry Level Insurance Data Analytics 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 ...

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 ...

World Insurance Associates LLC

Data Migration Analyst

$75K - $85K/yr

Company Overview World Insurance Associates ("World") is a unique financial services organization ... Position Overview We are seeking a Data Migration Analyst to support the successful migration of ...

TecTammina

Data Analyst

Chattanooga, TN · On-site

... analyst tool/IDQ Knowledge of XML and other databases like DB2, teradata and SQL ... Experience in insurance data models Qualifications Excellent written and verbal communication ...

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Entry Level Insurance Data Analytics information

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How much do entry level insurance data analytics jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for entry level insurance data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

What are some common challenges faced by entry-level professionals in insurance data analytics, and how can they be addressed?

Entry-level professionals in insurance data analytics often encounter challenges such as working with large, complex datasets, understanding industry-specific terminology, and aligning analytical findings with business objectives. To overcome these, it's important to develop strong data management and visualization skills, seek mentorship from experienced colleagues, and regularly communicate with underwriters, actuaries, and business teams to understand the context behind the numbers. Proactively participating in team meetings and taking advantage of on-the-job training can also help bridge knowledge gaps and foster professional growth.

What are the key skills and qualifications needed to thrive as an Entry Level Insurance Data Analytics professional, and why are they important?

To thrive as an Entry Level Insurance Data Analytics professional, you need foundational skills in statistics, data analysis, and proficiency with Excel or similar tools, often supported by a degree in mathematics, statistics, or a related field. Familiarity with data analytics software such as SQL, Python, R, and insurance industry databases is highly valuable. Strong problem-solving abilities, attention to detail, and effective communication skills set candidates apart in this role. These competencies are crucial for accurately interpreting insurance data, supporting business decisions, and conveying insights to both technical and non-technical stakeholders.

What is the difference between Entry Level Insurance Data Analytics vs Insurance Data Analyst?

AspectEntry Level Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's degree in data science, statistics, or related field; basic knowledge of analytics toolsBachelor's or higher in data analysis, statistics, or related; some roles prefer certifications
Work EnvironmentEntry-level roles in insurance companies, focusing on data collection and basic analysisMore experienced roles involving complex data modeling and reporting
Employer & Industry UsageInsurance companies, brokers, and agenciesInsurance firms, consulting agencies, and risk management companies

Entry Level Insurance Data Analytics positions focus on foundational data tasks within insurance firms, often requiring less experience and offering training opportunities. Insurance Data Analysts typically have more experience, handling advanced analysis and reporting. Both roles are essential in the insurance industry but differ mainly in complexity and responsibility.

What are entry level insurance data analytics jobs?

Entry level insurance data analytics jobs involve collecting, processing, and analyzing data to help insurance companies make better business decisions. Professionals in these roles typically use statistical tools and software to identify trends, assess risks, and support pricing or policy development. They may also prepare reports and visualizations to communicate findings to other teams. These positions are ideal for recent graduates with strong analytical skills who have an interest in the insurance industry.
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What cities are hiring for Entry Level Insurance Data Analytics jobs? Cities with the most Entry Level Insurance Data Analytics job openings:
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What job categories do people searching Entry Level Insurance Data Analytics jobs look for? The top searched job categories for Entry Level Insurance Data Analytics jobs are:
Entry Level Insurance Data Analytics jobs near you
Infographic showing various Entry Level Insurance Data Analytics job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 33% In-person, 34% Hybrid, and 33% Remote job distribution, with an average salary of $113,873 per year, or $54.7 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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