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Insurance Data Analytics Jobs in Utah (NOW HIRING)

Neighbor

Data Engineer

Lehi, UT · On-site

$107K - $129K/yr

Standardize analytics workflows by integrating software engineering best practices, including ... Medical, dental, and vision insurance * Generous PTO * 11 paid company holidays * 401(k) plan

Neighbor

Data Engineer

Lehi, UT

$107K - $129K/yr

Standardize analytics workflows by integrating software engineering best practices, including ... Medical, dental, and vision insurance * Generous PTO * 11 paid company holidays * 401(k) plan

Neighbor

Data Engineer

Lehi, UT

$107K - $129K/yr

Standardize analytics workflows by integrating software engineering best practices, including ... Medical, dental, and vision insurance * Generous PTO * 11 paid company holidays * 401(k) plan

eBay, Inc.

Risk & Insurance Analyst

Draper, UT · On-site

... analytics, and business intelligence tools to analyze risk data, identify trends and emerging ... Insurance Management: * Assist with the administration and management of the company's corporate ...

JT4, LLC

Operations Test and Data Analyst

Magna, UT · On-site

Develop basic data analysis tools, processes, or products for analysis * Analyze pre-test ... Medical, Dental, Vision Insurance * Benefits Active on Day 1 * Life Insurance * Health Savings ...

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Insurance Data Analytics information

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$49

$86

How much do insurance data analytics jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for insurance data analytics in Utah is $49.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.05 and $56.44 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Insurance Data Analytics position, and why are they important?

To thrive in Insurance Data Analytics, you need a solid understanding of data analysis, statistics, and insurance industry concepts, usually supported by a degree in mathematics, statistics, finance, or a related field. Proficiency with analytical tools like SQL, Python, R, and data visualization platforms (such as Tableau or Power BI), as well as certifications like CPCU or advanced analytics credentials, are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts translate complex data into actionable business insights. These skills are crucial for driving informed decision-making, risk assessment, and operational improvements within insurance organizations.

What are the typical responsibilities of someone working in Insurance Data Analytics?

Professionals in Insurance Data Analytics are responsible for collecting, cleaning, and analyzing large sets of insurance-related data to identify trends, assess risk, and inform business decisions. They commonly develop predictive models, generate reports, and provide actionable insights that help underwriting teams, actuarial staff, and business leaders optimize processes or pricing strategies. Day-to-day tasks may also include collaborating with IT and business units to define data requirements, presenting findings to non-technical stakeholders, and ensuring data integrity. This role often involves a mix of independent analysis and team-oriented projects, offering a dynamic and engaging work environment for problem solvers.

How is data analytics used in insurance?

In insurance, data analytics is used by professionals to assess risk, set premiums, detect fraud, and improve customer segmentation. Analysts utilize tools like statistical models and machine learning algorithms to interpret large datasets, enabling more accurate underwriting and claims management. Strong analytical skills and knowledge of data visualization are essential for effective decision-making in this field.

What does a data analyst do in insurance?

An insurance data analyst collects, processes, and analyzes insurance data to identify trends, assess risks, and support decision-making. They use tools like Excel, SQL, and data visualization software to create reports and models that improve underwriting, claims management, and pricing strategies.

How much does an insurance analyst make?

The average salary for an insurance analyst is around $65,000 to $85,000 per year, depending on experience, location, and industry. Entry-level roles typically start lower, while experienced analysts with specialized skills or certifications can earn higher salaries. Strong analytical skills and proficiency with data tools like Excel or SQL are often required.

Will AI replace a data analyst?

AI can automate routine data processing and analysis tasks, but the role of a data analyst, including those in insurance data analytics, involves interpreting complex data, providing insights, and making strategic decisions that require human judgment. Therefore, AI is more likely to augment rather than fully replace data analysts, who also need skills in data visualization, domain knowledge, and communication. Continuous learning and proficiency with analytics tools remain important for the role.

What is an Insurance Data Analytics job?

An Insurance Data Analytics job involves analyzing large volumes of insurance-related data to identify trends, assess risks, detect fraud, and improve decision-making. Professionals in this field use statistical models, machine learning, and data visualization tools to extract insights that help insurers optimize pricing, enhance customer experience, and reduce losses. They work with claims data, policyholder information, and external data sources to drive business strategy. Strong analytical skills, proficiency in data tools like SQL, Python, or R, and knowledge of insurance principles are essential for success in this role.

What are the most commonly searched types of Insurance Data Analytics jobs in Utah? The most popular types of Insurance Data Analytics jobs in Utah are:
What are popular job titles related to Insurance Data Analytics jobs in Utah? For Insurance Data Analytics jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Insurance Data Analytics jobs in Utah look for? The top searched job categories for Insurance Data Analytics jobs in Utah are:
What cities in Utah are hiring for Insurance Data Analytics jobs? Cities in Utah with the most Insurance Data Analytics job openings:
Insurance Data Analytics jobs near you
Infographic showing various Insurance Data Analytics job openings in Utah as of July 2026, with employment types broken down into 1% Internship, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $103,667 per year, or $49.8 per hour.
Data Engineer

Data Engineer

Neighbor

Lehi, UT • On-site

$107K - $129K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 5 days ago

Job description

At Neighbor, we're building the largest hyperlocal marketplace the world has ever seen. We've raised over $75 million from top-tier investors such as Andreessen Horowitz and the CEOs of DoorDash, StockX, and Uber. Our marketplace is already flourishing in all 50 states and we're just getting started!
As a Data Engineer, you will be the core engineering resource responsible for building, scaling, and optimizing the data infrastructure that transforms raw events into high-fidelity, actionable intelligence. You will pioneer a foundation of engineering excellence, enabling the entire organization to make reliable, data-driven decisions at scale across all 50 states.
This engineering resource will be the cornerstone of our data infrastructure, responsible for extraction, transform, and load of the data that powers our nation-wide, best-in-class marketplace. By implementing software engineering best practices and scalable solutions, this role is critical in empowering the CEO, executive team, managers, and individual contributors with the robust and trustworthy intelligence needed to scale and innovate across our marketplace.
Primary Responsibilities
  • Design, implement, and maintain scalable data transformation layers and code-first orchestration frameworks to ensure the delivery of high-fidelity, reusable data models
  • Design and build robust pipelines to ingest data from diverse sources (APIs, logs, relational DBs)
  • Ensure the reliable and timely execution of all critical data pipelines (ETLs/ELTs) to maintain data integrity and freshness
  • Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols
  • Develop and refine a robust semantic layer to facilitate self-service analytics, enabling stakeholders to derive insights without exposure to underlying architectural complexities
  • Monitor and optimize cloud compute utilization and data model performance to ensure high availability and low-latency reporting during periods of rapid data scaling
  • Serve as a strategic technical partner to leadership across Product, Engineering, Marketing, and Finance to align data infrastructure with organizational objectives
  • Become a subject matter expert on the product ecosystem, user behavior, and marketing life cycles to better translate raw data into business value
  • Serve as a versatile technical resource capable of stepping into the Data Analyst capacity when necessary-performing deep-dive quantitative analysis and building sophisticated visualizations to support executive decision-making
  • Mentor the data analytics team on advanced technical methodologies to foster a culture of engineering excellence and data autonomy

Qualifications
  • 3+ years of experience in data engineering or analytics engineering
  • Bachelor's degree in quantitative and/or technical fields (Math, Physics, Statistics, Economics, Computer Science, Engineering, etc.) OR 5+ years work experience as a Data Engineer
  • Expert-level mastery of SQL, with the ability to write, tune, and optimize complex queries for high-volume environments
  • Strong command of at least one major programming language used for data processing
  • Hands-on experience designing and maintaining data lakes or cloud-based data warehouses
  • Deep understanding of data integration patterns, including data ingestion, transformation, and automated cleansing (ETL/ELT)
  • Experience applying scientific, mathematical, or statistical techniques to analyze data and build predictive models
  • Advanced ability to translate complex datasets into actionable narratives using modern business intelligence and reporting tools
  • A proven track record of using quantitative analysis to solve ambiguous problems and drive strategic decision-making in a fast-paced environment
  • Exceptional ability to collaborate with non-technical stakeholders, translating business requirements into technical specs and vice versa

Benefits
  • Generous Stock options
  • Medical, dental, and vision insurance
  • Generous PTO
  • 11 paid company holidays
  • 401(k) plan
  • Infant care leave
  • On-site gym/showers open 24/7

About Neighbor:
Neighbor is the largest and most comprehensive marketplace for self storage and parking, with listings in almost every U.S. city. From storage facilities to neighborhood garages, driveways, and RV spots, Neighbor brings every option together in one simple search. Come help us disrupt the $500 billion storage and parking industry! This is a unique opportunity to join a fast-growing, VC-backed tech startup. You will be part of a an extremely talented, hardworking and passionate team committed to changing the world one neighbor at a time.
Neighbor is an equal opportunity employer and is committed to providing a positive interview experience for every candidate. If accommodations due to a disability or medical condition are needed, connect with us via email at [email protected]. Check out our careers page to get to know us better as you think about your next step at Neighbor!
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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