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Executive Insurance Data Analytics Jobs (NOW HIRING)

Insurance Data Analyst

Seattle, WA ยท On-site

$88K - $123K/yr

Insurance Data Analyst Location: United States Workplace Type: Remote About the Job The future is ... analytics, or related roles. * Strong SQL skills with hands-on experience in BigQuery and/or SQL ...

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 ...

Insurance Data Analyst

Seattle, WA ยท On-site +1

$88K - $123K/yr

Insurance Data Analyst Location: United States Workplace Type: Remote About the Job The future is ... analytics, or related roles. * Strong SQL skills with hands-on experience in BigQuery and/or SQL ...

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 ...

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 ...

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 ...

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 ...

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Executive Insurance Data Analytics information

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$26.5K

$93.6K

$184K

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

As of Aug 8, 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.

How does an executive insurance data analytics 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 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.

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 is an executive insurance data analytics?

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 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:
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Contractor

Re-posted 25 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.