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Executive Insurance Data Analytics Jobs (NOW HIRING)

Orion180

Senior Insurance Data Analyst

Irving, TX · On-site

$82.60K - $104.20K/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 ...

VAST Data

Account Executive - Insurance

New York, NY · On-site

Description VAST Data is looking for an Account Executive to join our growing team! This is a great ... data analysis and AI training and inference. Designed from the ground up to make AI simple to ...

Everest

AVP, Data & Analytics Product Owner

Warren, NJ · Hybrid

$201K - $225K/yr

Provide strategic product ownership for Insurance data and analytics, with endtoend accountability for product vision, roadmap, prioritization, delivery, adoption, and ongoing value realization.

VAST Data

Account Executive - Insurance

Boston, MA · On-site

Description VAST Data is looking for an Account Executive to join our growing team! This is a great ... data analysis and AI training and inference. Designed from the ground up to make AI simple to ...

TecTammina

Data Analyst

Chattanooga, TN

Experience in insurance data models Qualifications Excellent written and verbal communication ... executive staff and team members apprised of goals, project status, and resolve issues and ...

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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Executive Insurance Data Analytics information

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

As of May 31, 2026, the average yearly pay for executive insurance data analytics in the United States is $93,552.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,000.00 and $120,500.00 per year, depending on experience, location, and employer.

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

To excel as an Executive in Insurance Data Analytics, you need expertise in statistical analysis, data modeling, insurance industry knowledge, and often an advanced degree in data science or actuarial science. Familiarity with analytics platforms like SAS, SQL, Python, and business intelligence tools, as well as certifications such as CPCU or data analytics credentials, are typically required. Strategic thinking, leadership, and strong communication skills help drive insights and influence organizational decision-making. These skills are crucial for transforming complex data into actionable strategies that enhance profitability and manage risk in the insurance sector.

How does the Executive Insurance Data Analytics role typically collaborate with other departments to drive business decisions?

In the Executive Insurance Data Analytics role, collaboration with departments such as underwriting, claims, and product development is essential. You will regularly work with cross-functional teams to interpret complex data, identify trends, and provide actionable insights that support strategic business decisions. Clear communication and the ability to translate analytics into business terms are key, as you will often present findings to both technical and non-technical stakeholders. This collaborative approach not only helps improve operational efficiency but also ensures data-driven decision-making across the organization.

What is an Executive Insurance Data Analytics professional?

An Executive Insurance Data Analytics professional is a senior leader who oversees the collection, analysis, and interpretation of data to guide decision-making within insurance organizations. They leverage advanced analytics, data science, and business intelligence to identify trends, assess risks, and optimize business strategies. Their role often involves setting data strategy, ensuring data quality, and communicating insights to stakeholders to improve profitability and efficiency. They typically collaborate with IT, actuarial, underwriting, and claims teams to drive data-driven transformation across the company.

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

AspectExecutive Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's or higher in Data Science, Statistics, or related field; experience in insurance analyticsBachelor's in Data Science, Statistics, or related field; entry to mid-level experience
Work EnvironmentStrategic, leadership-focused, often in management teamsOperational, data-focused, often in analytics teams
Employer & Industry UsageInsurance companies, consulting firms, risk management firmsInsurance companies, brokers, third-party analytics providers

Executive Insurance Data Analytics roles focus on strategic decision-making and leadership in insurance data projects, while Insurance Data Analysts handle data collection, analysis, and reporting at operational levels. Both roles require similar educational backgrounds but differ in scope and responsibility.

What cities are hiring for Executive Insurance Data Analytics jobs? Cities with the most Executive Insurance Data Analytics job openings:
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 Executive Insurance Data Analytics jobs? States with the most job openings for Executive Insurance Data Analytics jobs include:
Executive Insurance Data Analytics jobs near you

Insurance Data Analyst

BizTek People, Inc. | APA International Placement Consultants

Portland, OR • On-site

Contractor

Posted 16 days ago

Job description

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 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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