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Entry Level Insurance Data Analytics Jobs in Chicago, IL

Guidehouse

Data & Analytics Consultant

Chicago, IL · On-site

$89K - $148K/yr

Translate business questions into data-driven analyses, dashboards, reports, and actionable ... Medical, Rx, Dental & Vision Insurance * Personal and Family Sick Time & Company Paid Holidays

New

LHH US

Data Analyst

Chicago, IL · On-site

$30 - $35/hr

Data Analyst (Entry-Level) Chicago, IL (Hybrid) $30.00 - $35.00 per hour Contract / Contract-to ... life insurance, short-term disability, additional voluntary benefits, EAP program, commuter ...

New

LHH US

Data Analyst

Chicago, IL · On-site

$30 - $35/hr

Data Analyst (Entry-Level) Chicago, IL (Hybrid) $30.00 - $35.00 per hour Contract / Contract-to ... life insurance, short-term disability, additional voluntary benefits, EAP program, commuter ...

New

Core Specialty

Actuarial Data Analyst

Chicago, IL · Hybrid

$70K - $75K/yr

- The Core Specialty Data Analytics Team is looking for a Data Analyst. This dynamic role is ... We offer medical, dental, vision, and life insurances; short and long-term disability; a Company ...

Core Specialty

Actuarial Data Analyst

Chicago, IL · On-site

$70K - $75K/yr

The Core Specialty Data Analytics Team is looking for a Data Analyst. This dynamic role is ... We offer medical, dental, vision, and life insurances; short and long-term disability; a Company ...

Kforce Technology Staffing

Data Analyst

Chicago, IL

Bachelor's degree in Finance, Accounting, Economics, Data Analytics, or a related field * 2+ years ... We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and ...

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Entry Level Insurance Data Analytics information

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$25

$56

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How much do entry level insurance data analytics jobs pay per hour?

As of May 29, 2026, the average hourly pay for entry level insurance data analytics in Chicago, IL is $56.40, according to ZipRecruiter salary data. Most workers in this role earn between $45.34 and $63.89 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Insurance Data Analytics professional, and why are they important?

To thrive as an Entry Level Insurance Data Analytics professional, you need foundational skills in statistics, data analysis, and proficiency with Excel or similar tools, often supported by a degree in mathematics, statistics, or a related field. Familiarity with data analytics software such as SQL, Python, R, and insurance industry databases is highly valuable. Strong problem-solving abilities, attention to detail, and effective communication skills set candidates apart in this role. These competencies are crucial for accurately interpreting insurance data, supporting business decisions, and conveying insights to both technical and non-technical stakeholders.

What are some common challenges faced by entry-level professionals in insurance data analytics, and how can they be addressed?

Entry-level professionals in insurance data analytics often encounter challenges such as working with large, complex datasets, understanding industry-specific terminology, and aligning analytical findings with business objectives. To overcome these, it's important to develop strong data management and visualization skills, seek mentorship from experienced colleagues, and regularly communicate with underwriters, actuaries, and business teams to understand the context behind the numbers. Proactively participating in team meetings and taking advantage of on-the-job training can also help bridge knowledge gaps and foster professional growth.

What are entry level insurance data analytics jobs?

Entry level insurance data analytics jobs involve collecting, processing, and analyzing data to help insurance companies make better business decisions. Professionals in these roles typically use statistical tools and software to identify trends, assess risks, and support pricing or policy development. They may also prepare reports and visualizations to communicate findings to other teams. These positions are ideal for recent graduates with strong analytical skills who have an interest in the insurance industry.

What is the difference between Entry Level Insurance Data Analytics vs Insurance Data Analyst?

AspectEntry Level Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's degree in data science, statistics, or related field; basic knowledge of analytics toolsBachelor's or higher in data analysis, statistics, or related; some roles prefer certifications
Work EnvironmentEntry-level roles in insurance companies, focusing on data collection and basic analysisMore experienced roles involving complex data modeling and reporting
Employer & Industry UsageInsurance companies, brokers, and agenciesInsurance firms, consulting agencies, and risk management companies

Entry Level Insurance Data Analytics positions focus on foundational data tasks within insurance firms, often requiring less experience and offering training opportunities. Insurance Data Analysts typically have more experience, handling advanced analysis and reporting. Both roles are essential in the insurance industry but differ mainly in complexity and responsibility.

What are the most commonly searched types of Insurance Data Analytics jobs in Chicago, IL? The most popular types of Insurance Data Analytics jobs in Chicago, IL are:
What are popular job titles related to Entry Level Insurance Data Analytics jobs in Chicago, IL? For Entry Level Insurance Data Analytics jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Entry Level Insurance Data Analytics jobs in Chicago, IL look for? The top searched job categories for Entry Level Insurance Data Analytics jobs in Chicago, IL are:
Entry Level Insurance Data Analytics jobs near you
Infographic showing various Entry Level Insurance Data Analytics job openings in Chicago, IL as of May 2026, with employment types broken down into 2% As Needed, 67% Full Time, 20% Part Time, and 11% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $117,306 per year, or $56.4 per hour.

Entry Level Operations Data Analyst

Benda Infotech

Chicago, IL

$77K - $82K/yr

Full-time

Posted yesterday

Job description

Role Summary

We are seeking an Entry Level Operations Data Analyst with strong analytical skills, attention to detail, and a problem-solving mindset. This role will support business operations and decision-making by transforming raw data into actionable insights. The Operations Data Analyst will work with large and complex data sets, develop reports and dashboards, and contribute to data quality, automation, and documentation initiatives across the organization.

Key Responsibilities
  • Interpret and analyze structured data using industry best practices to support operational and business needs
  • Identify trends, patterns, and anomalies in complex data sets and clearly communicate findings to stakeholders
  • Extract, cleanse, validate, and transform data from primary and secondary data sources
  • Design, develop, and maintain business intelligence dashboards and recurring operational reports
  • Support the development and execution of data strategies that improve data quality, consistency, and usability
  • Collaborate with operations, technology, and business teams to ensure accurate and reliable reporting
  • Prepare and maintain technical documentation, data definitions, and process documentation
  • Assist in identifying opportunities for process improvements and operational efficiencies through data analysis
Qualifications & RequirementsMinimum Qualifications
  • 0–2 years of hands-on experience in data analytics, reporting, operations support, or data automation
  • Experience preparing, blending, and analyzing data from multiple sources
  • Proficiency in:
    • Python, including data analysis libraries
    • SQL for querying relational databases
    • Power BI for dashboard development and data visualization
    • Microsoft Excel (Advanced), including formulas, pivot tables, and data modeling
  • Solid understanding of database concepts and data structures
  • Strong written and verbal communication skills, with the ability to translate analytical results into clear business insights
  • Demonstrated ability to manage multiple priorities, meet deadlines, and work effectively in a fast-paced environment
Preferred Qualifications
  • Internship, academic project, or professional experience in operations analytics, banking, financial services, or a highly regulated industry
  • Familiarity with data governance, data quality controls, or reporting concepts
  • Experience documenting workflows, business rules, and analytical methodologies
  • Exposure to automation or process improvement initiatives related to operations or analytics
  • Ability to collaborate effectively with both technical and non-technical stakeholders