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Remote Insurance Data Analytics Jobs in Boise, ID

Data Analyst V

Boise, ID ยท Remote

$130K/yr

USA Remote Responsibilities * Work with large and complex datasets to solve challenging problems using various analytical and statistical approaches. * Synthesize and analyze customer feedback from ...

Over 300 leading healthcare organizations have come to rely on MedInsight analytic solutions for ... This position is fully remote, while occasional travel may be required. Primary Responsibilities:

Participate in remote assignments or attend on-site sessions when required * Follow project ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Participate in remote assignments or attend on-site sessions when required * Follow project ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Deliver timely and accurate information regarding Financial Statements & Analytics Reporting ... Validate investment data against available third-party market data sources and show proficiency in ...

Ability to analyze data and develop client-facing deliverables that are informative, clear, and ... Location This role is ideally based in Seattle, Washington, but remote work within the United ...

The Reconciliation Analyst is responsible for comparing investment portfolio data from external ... Competitive medical, dental, vision, and life insurance benefits * Maternity and paternity leave

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Remote Insurance Data Analytics information

See Boise, ID salary details

$23

$52

$89

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

As of Jun 25, 2026, the average hourly pay for remote insurance data analytics in Boise, ID is $52.11, according to ZipRecruiter salary data. Most workers in this role earn between $41.88 and $59.04 per hour, depending on experience, location, and employer.

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.

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.

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 are the key skills and qualifications needed to thrive as a Remote Insurance Data Analytics professional, and why are they important?

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.
What are the most commonly searched types of Insurance Data Analytics jobs in Boise, ID? The most popular types of Insurance Data Analytics jobs in Boise, ID are:
What job categories do people searching Remote Insurance Data Analytics jobs in Boise, ID look for? The top searched job categories for Remote Insurance Data Analytics jobs in Boise, ID are:
Infographic showing various Remote Insurance Data Analytics job openings in Boise, ID as of June 2026, with employment types broken down into 74% Full Time, and 26% Part Time. Highlights an 48% In-person, 5% Hybrid, and 47% Remote job distribution, with an average salary of $108,380 per year, or $52.1 per hour.

Data Analyst V

H R PUNDITS INC

Boise, ID โ€ข Remote

$130K/yr

Full-time

Posted 9 days ago


Job description

Data Analyst V
Location: USA Remote
Responsibilities
  • Work with large and complex datasets to solve challenging problems using various analytical and statistical approaches.
  • Synthesize and analyze customer feedback from multiple sources (e.g., surveys, digital analytics, behavioral, and operational data) across end-to-end customer journeys to identify trends, pain points, and areas for improvement.
  • Apply advanced statistical modeling, machine learning, and natural language processing (NLP) to analyze large-scale customer support interactions (e.g., chat logs, call transcripts, support tickets) and extract actionable insights.
  • Use clustering and segmentation techniques to identify common customer issues and recommend targeted solutions or self-service resources.
  • Develop and maintain robust reporting and dashboards to track customer experience metrics and KPIs.
  • Integrate customer feedback data with other transactional, operational, and Req Intake Template behavioral data sources to create a comprehensive picture of customer experience drivers.
  • Advocate for customers and influence corrective actions
Please submit 10+ years profiles only
Must Have
1 Very technical with marketing background
2 Customer segmentation for marketing
3 Customer support
4 Comfortable with temporary tables in SQL
5 Strong skills in Python Pandas and data structures
6 Experience with data modeling (regression, NLP).

This is a remote position.