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Remote Insurance Data Analytics Jobs (NOW HIRING)

With expertise in digital media supply chain, data & analytics, IP & rights management, broadcast ... Remote & Hybrid Work While remote or hybrid work may be permitted for certain projects, client ...

... analytics into production on the Azure Databricks platform. LOCATION: Remote, or hybrid in any of ... data from a variety of insurance-related sources. • Perform exploratory data analysis to identify ...

Remote Duration: 6 months- Initially 20- 30 hours a week. Data Analyst Role and responsibilities ... Mid-level and more data analytics than PM * Parts/Industry experience - From the client: I'd add B2 ...

Required : • 3+ years of experience in the insurance industry, including roles in underwriting, claims, product, actuarial support, or data analytics. • Hands-on experience with SQL, Python, R ...

Sr Analyst - Data Analytics

VA · On-site +1

$86K - $109K/yr

This is a remote position. Essential Duties and Responsibilities: - Develop and deploy advanced ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Atlanta, GA - Hybrid/Remote Experience: 10 Years Role Overview We are seeking an experienced ... Insurance, data analytics, SQL, and customer data transformation initiatives. This role will ...

Data Engineer

$117K - $140K/yr

Remote-first flexibility. * The opportunity to help build an AI-native product from the ground up ... our analytics and AI products, from ingesting messy, real-world insurance data to the ...

... insurance property / casualty lines is REQUIRED.) Join our Enterprise Data & Analytics team and ... analytics into production on the Azure Databricks platform. LOCATION: Remote, or hybrid in any of ...

Showing results 41-60

Remote Insurance Data Analytics information

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$24

$54

$94

How much do remote insurance data analytics jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for remote 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 is remote insurance data analytics?

Remote insurance data analytics is the practice of analyzing insurance-related data, such as claims, risk assessments, and customer information, from a location outside of a traditional office setting. Professionals in this field use statistical methods, data mining, and machine learning tools to identify patterns, detect fraud, and help insurance companies make data-driven decisions. This remote role often requires proficiency in data analysis tools like SQL, Python, or R, and a strong understanding of insurance industry concepts. Remote insurance data analysts collaborate with teams virtually to provide insights and support business strategies, making it a flexible career option.

What are the key skills and qualifications needed to thrive as a remote insurance data analytics professional?

To excel in Remote Insurance Data Analytics, you need strong analytical skills, a background in statistics or mathematics, and typically a degree in data science, actuarial science, or a related field. Familiarity with data analysis tools like SQL, Python, R, and specialized insurance analytics platforms such as SAS or Tableau, as well as relevant certifications, is highly valuable. Attention to detail, problem-solving abilities, and effective communication set candidates apart in this role. These skills are crucial for transforming complex insurance data into actionable insights that drive informed business decisions and risk assessments.

How do remote insurance data analytics professionals typically collaborate with cross-functional teams to drive business insights?

Remote Insurance Data Analytics professionals often work closely with underwriters, actuaries, claims managers, and IT teams to gather data requirements, interpret findings, and implement data-driven solutions. Collaboration usually happens through virtual meetings, collaborative dashboards, and project management tools to ensure clear communication and alignment on objectives. This cross-functional approach helps identify trends, optimize risk assessments, and support strategic decision-making within the organization. Building strong relationships with team members across departments is key to successfully translating analytical results into actionable business strategies.

What is the difference between Remote Insurance Data Analytics vs Remote Insurance Underwriter?

AspectRemote Insurance Data AnalyticsRemote Insurance Underwriter
Required CredentialsBachelor's in Data Science, Statistics, or related field; often certifications in data analysis or analyticsBachelor's in Business, Finance, or related; often requires insurance licensing or certifications
Work EnvironmentPrimarily data analysis, modeling, and reporting; often collaborative with IT and actuarial teamsAssessing risks, reviewing applications, making underwriting decisions; involves communication with agents and clients
Employer & Industry UsageUsed across insurance companies, reinsurers, and brokers for data-driven decision makingUsed by insurance carriers to evaluate and approve policies

Remote Insurance Data Analytics focuses on analyzing insurance data to inform business decisions, while Remote Insurance Underwriters evaluate individual insurance applications to determine coverage. Both roles are essential in the insurance industry but differ in daily tasks and required skills.

More about Remote Insurance Data Analytics jobs

What cities are hiring for Remote Insurance Data Analytics jobs?

Cities with the most Remote 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 Remote Insurance Data Analytics jobs?

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

Infographic showing various Remote Insurance Data Analytics job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.

Full-time

Posted 12 days ago


Job description

Primeritus Financial Services is a national provider of repossession management, remarketing, titled, and skip tracing services to the automotive finance industry in the United States and Puerto Rico. Primeritus provides clients with value-added, outsourced repossession management skip tracing investigations, and remarketing services by leveraging a national network of certified agents and unique investigative techniques to quickly and reliably secure customers' collateral. Through effective leadership, service, and performance, Primeritus Financial Services offers the trifecta of repossession services: locate, recover, and remarket.
The Data Analytics Lead shapes how Primeritus uses data. This person architects our BI and analytics platform, teaches business users to think more broadly about their data and find their own answers, and leads a small reporting/analyst team. Success is measured less by the volume of analysis this person personally produces, and more by how well-equipped the business becomes to use data on its own - alongside a scalable analytics architecture and a growing team. This position is remote and open to candidates located in the Denver, CO; Dallas, TX; Nashville, TN; and Raleigh, NC markets.
Key Responsibilities
Data Education & Enablement
• Teach and coach business users on data best practices - how to frame the right questions, interpret results correctly, and avoid common analytical pitfalls.
• Help teams look more broadly at their data: encourage thinking beyond the immediate ask to underlying trends, context, and root causes.
• Build reusable frameworks, documentation, and training materials that raise the analytical maturity of the organization over time.
• Partner with product, analytics, and leadership teams to translate one-off questions into repeatable, self-service answers.
• Step in personally on complex or ambiguous analysis when needed, modeling best practice for others to learn from.
BI & Analytics Architecture
• Own the target-state vision for Primeritus's BI/analytics architecture and set the roadmap to get there.
• Design and evolve data models, reporting structures, and integrations that support product platforms, analytics, and regulatory requirements.
• Expand self-service analytics capabilities - including natural-language and AI-assisted query tools - so business users can access and explore their own data with less dependence on the BI team.
• Evaluate and recommend BI/analytics tooling and platform improvements as the business and data needs grow.
• Monitor, optimize, and troubleshoot reporting and data processing performance.
Leadership & Mentorship
• Lead a small team of reporting/analyst team members - providing direction, technical coaching, and career development.
• Review the team's analysis and reporting work for accuracy, clarity, and business relevance.
• Serve as the go-to technical authority on analytics and data-related decisions across product and technology teams.
Governance & Compliance
• Define and enforce data governance standards, including data quality, lineage, and metadata management.
• Ensure architecture and reporting practices support financial-industry compliance, security, privacy, and auditability requirements.
• Collaborate with security, risk, and compliance partners to embed controls into architecture and reporting.
Technical Skills & Capabilities
Core Technologies
• 8+ years of experience in BI development, data analysis, or analytics architecture.
• Strong expertise in TSQL, Power BI, and DAX; SSIS/SSAS experience a plus.
• Experience with Azure Data Services (ADF, Azure SQL Database, Synapse) or an equivalent cloud data platform.
• Solid understanding of data warehouse and reporting architecture.
• Experience resolving complex data quality and performance issues.
AI & Emerging Technology
• Experience using AI/LLM tools to accelerate analysis, reporting, or documentation (e.g., Copilot in Power BI, AI-assisted SQL or DAX generation).
• Understanding of how natural-language/AI query interfaces work over structured data, sufficient to architect, evaluate, and govern them.
• Comfort piloting and assessing emerging AI tooling for BI and self-service analytics, and separating real capability from hype.
Analytics, Communication & Teaching
• Ability to analyze large, complex datasets and translate them into meaningful, decision-ready insights.
• Strong reporting and visualization skills using Power BI, Power Apps, and Excel.
• Excellent written and verbal communication skills; able to explain technical concepts to non-technical audiences.
• Experience training, coaching, or upskilling business users on data literacy or analytical best practices.
• Demonstrated ability to tell clear, compelling stories from data.
Qualifications
Required
• Bachelor's or Master's degree in Computer Science, Statistics, Data Analytics, or a related field (or equivalent experience).
• 5+ years of experience developing analytics, data platforms, or decision-support solutions.
• Experience in financial services or another highly regulated industry.
• Experience mentoring or providing technical direction to reporting/analyst staff.
• Experience teaching or coaching non-technical business users on how to work with and interpret data.
Preferred
• Experience supporting product-led or platform-based organizations.
• Familiarity with cloud-native analytics ecosystems.
• Relevant cloud, data architecture, or analytics certifications.
Success Looks Like
• Business users ask sharper questions and think more broadly about their data, rather than relying solely on the BI team.
• Executives and business teams rely on trusted, timely, data-driven insight to guide decisions.
• The BI/analytics architecture scales with business growth and regulatory change.
• Business users increasingly self-serve data and answers, reducing ad hoc load on the BI team.
• The team members grow in capability and confidence under this person's mentorship.
Primeritus is an Equal Opportunity employer and all qualified applicants will receive consideration to employment without regard to race, color, religion, gender, pregnancy, sexual orientation, national origin, age, or protected veteran or disability status.