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Insurance Data Analyst Jobs in Indiana (NOW HIRING)

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Insurance Data Analyst information

See Indiana salary details

$32.4K

$78.6K

$129.4K

How much do insurance data analyst jobs pay per year?

As of Jun 19, 2026, the average yearly pay for insurance data analyst in Indiana is $78,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $92,300.00 per year, depending on experience, location, and employer.

What does a data analyst do at an insurance company?

An insurance data analyst collects, analyzes, and interprets data related to policies, claims, and customer information to identify trends and support decision-making. They use tools like Excel, SQL, and data visualization software to create reports and improve underwriting, pricing, and risk assessment processes.

What is the difference between Insurance Data Analyst vs Actuary?

AspectInsurance Data AnalystActuary
Required CredentialsBachelor's degree in statistics, data science, or related field; often certifications like CAP or CPCUBachelor's degree in mathematics, statistics, or actuarial science; professional actuarial exams and credentials (e.g., ASA, FSA)
Work EnvironmentData analysis teams within insurance companies, focusing on data modeling and reportingActuarial departments, focusing on risk assessment, pricing, and reserving
Employer & Industry UsageInsurance companies, brokers, and consulting firmsInsurance companies, consulting firms, government agencies

While both roles involve working with insurance data, Insurance Data Analysts focus on data collection, analysis, and reporting, whereas Actuaries specialize in risk modeling and financial forecasting using advanced mathematics and actuarial exams. The roles often collaborate but serve different strategic functions within insurance organizations.

Do insurance companies need a data analyst?

Insurance companies rely on data analysts to interpret large datasets, assess risk, and support decision-making processes. Data analysts use tools like SQL and Excel, and often require knowledge of insurance industry metrics to improve underwriting, claims processing, and customer insights.

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

To thrive as an Insurance Data Analyst, you need strong analytical skills, proficiency in statistics, and a background in mathematics, finance, or a related field, often supported by a relevant degree. Familiarity with data analysis tools such as SQL, Excel, Python, and data visualization platforms, as well as knowledge of insurance-specific databases and certifications like CPCU or AIDA, is highly valued. Attention to detail, problem-solving, and effective communication are crucial soft skills for interpreting complex data and presenting insights to stakeholders. These skills ensure accurate risk assessment, data-driven decision-making, and effective support of business objectives in the insurance industry.

How does an Insurance Data Analyst typically collaborate with underwriters and actuaries?

Insurance Data Analysts frequently work alongside underwriters and actuaries to provide data-driven insights that inform risk assessment and pricing decisions. Analysts gather, clean, and interpret large sets of policyholder and claims data, then present actionable findings through reports or dashboards. Regular meetings and joint projects ensure that underwriters and actuaries have the most accurate, up-to-date information to make decisions, and that data models align closely with business needs. Strong communication and teamwork skills are essential for success in this collaborative environment.

What does an Insurance Data Analyst do?

An Insurance Data Analyst is responsible for collecting, processing, and analyzing data related to insurance policies, claims, customer behavior, and market trends. They use statistical tools and software to identify patterns, assess risks, and provide actionable insights that help insurance companies make informed decisions. Their work supports pricing strategies, fraud detection, customer retention, and overall business performance. Insurance Data Analysts often collaborate with underwriters, actuaries, and business managers to optimize processes and improve profitability.

Is AI replacing data analysts?

AI is transforming the role of insurance data analysts by automating routine data processing and analysis tasks, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can handle large datasets efficiently, human expertise remains essential for interpreting results, ensuring data quality, and applying domain knowledge. The role continues to evolve with skills in data management, programming, and AI tools being increasingly valuable.

Is 40 too late for data science?

For an Insurance Data Analyst, age is not a barrier to entering data science. Many professionals transition into data roles later in their careers by acquiring relevant skills such as programming, statistics, and data visualization, often through online courses or certifications. Experience in insurance or related fields can also be valuable in this career shift.
What are popular job titles related to Insurance Data Analyst jobs in Indiana? For Insurance Data Analyst jobs in Indiana, the most frequently searched job titles are:
Infographic showing various Insurance Data Analyst job openings in Indiana as of June 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 90% In-person, 4% Hybrid, and 6% Remote job distribution, with an average salary of $78,637 per year, or $37.8 per hour.
Remote Investment Analyst - AI Trainer ($50-$60 per hour)

Remote Investment Analyst - AI Trainer ($50-$60 per hour)

Data Annotation

Elkhart, IN • Remote

$50 - $60/hr

Full-time, Part-time, Contractor

This job post has expired today. Applications are no longer accepted.


Job description

DataAnnotation is committed to creating high-quality AI. Join our team to help train the next generation of AI while enjoying the flexibility of remote work and the freedom to set your own schedule. This role is designed to fit a variety of lifestyles — whether you’re looking to contribute part-time alongside a current position, pursue it full-time, or engage periodically as a flexible professional opportunity.

We're currently expanding into an exciting new area – teaching AI Assistant models to be a more useful tool for finance professionals. We're seeking experienced finance professionals with advanced degrees (MBA+) and professional experience to use their expertise to help shape how AI understands financial principles and decision-making.

We’re growing a team of finance experts, and as the team grows, so will your opportunities. In this role, you might:

  • Review and improve AI Assistant answers to questions about macro trends, corporate finance, and capital markets
  • Leverage your education and work experience to check the reasoning and accuracy of an AI Assistant's work
  • Push the models with complex, real-world scenarios and edge cases to see where their reasoning holds up – and where it doesn’t.
  • Share clear, structured feedback to help make each new version of the AI smarter and more reliable.

To succeed in this position, you should have expert-level financial reasoning and formal training in a finance-related discipline. A Master’s or PhD (completed or in progress) is strongly preferred. Relevant backgrounds include Financial Accounting, Investment Banking, Corporate Development, Wealth Management, and Insurance Planning.

Benefits:

  • This is a full-time or part-time REMOTE position
  • You’ll be able to choose which projects you want to work on
  • You can work on your own schedule
  • Projects are paid hourly starting at USD $50-$60 per hour, with bonuses on high-quality and high-volume work

Responsibilities:

  • Give AI chatbots diverse and complex problems and evaluate their outputs
  • Evaluate the quality produced by AI models for correctness and performance

Qualifications:

  • Fluency in English (native or bilingual level)
  • Detail-oriented
  • Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises related to finance management
  • A current, in progress, or completed Masters and/or PhD is is preferred but not required

Note: Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. This is an independent contract position.