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Entry Level Insurance Data Analytics Jobs in Chicago, IL

Synergie Systems

Entry-Level Data Analyst

Chicago, IL · On-site

Job Title: Entry-Level Data Analyst Location: Chicago, IL Job Type: Only W2 · Collect, clean, and ... Qualifications: · Bachelor's degree in computer science, Data Analytics, Statistics, Mathematics ...

Benda Infotech

Data Analyst

Chicago, IL

... data analytics, business intelligence, and data-driven decision-making. Key Responsibilities ... Medical, dental, and vision insurance * Paid holidays and generous paid time off * Retirement ...

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Entry Level Insurance Data Analytics information

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$56

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

As of Aug 28, 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 is an entry level insurance data analytics job?

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 are the key skills and qualifications needed to thrive as an entry level insurance data analytics professional?

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 insurance data analytics professionals, 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 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 does an entry level insurance data analyst do in insurance?

An entry level insurance data analyst collects, organizes, and analyzes insurance data to identify trends, assess risks, and support decision-making. They often use tools like Excel, SQL, or data visualization software and work closely with underwriters and actuaries to improve underwriting processes and pricing strategies.

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 July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $117,306 per year, or $56.4 per hour.

Entry-Level Data Analyst

Chicago, IL • On-site

Synergie Systems
Recruiting and Staffing Services • 11 - 50 employees
Learn more about Synergie Systemsexternal

Other

Posted 11 days ago

Job description

Job Title: Entry-Level Data Analyst

Location: Chicago, IL

Job Type: Only W2

Job Description:

·       Collect, clean, and analyze data from multiple sources.

·       Write SQL queries to extract and manipulate data.

·       Create reports and dashboards using tools such as Power BI or Tableau.

·       Perform data validation and identify data quality issues.

·       Analyze trends, patterns, and business performance metrics.

·       Prepare daily, weekly, and monthly reports.

·       Support senior analysts and business teams with ad-hoc data requests.

·       Maintain and update datasets, reports, and dashboards.

·       Communicate analytical findings to technical and non-technical stakeholders.

·       Document data sources, processes, and reporting procedures.

·       Assist with automating repetitive reporting tasks.

Required Skills:

·       SQL — SELECT, WHERE, JOIN, GROUP BY, subqueries, aggregations.

·       Excel — PivotTables, VLOOKUP/XLOOKUP, formulas, charts, data cleaning.

·       Basic understanding of data analysis and statistics.

·       Familiarity with Power BI or Tableau.

·       Good analytical and problem-solving skills.

·       Strong attention to detail.

·       Good written and verbal communication skills.

Preferred Skills:

·       Python, especially Pandas and NumPy.

·       Power BI/DAX or Tableau.

·       Basic knowledge of relational databases.

·       Understanding of ETL/data pipelines.

·       Basic knowledge of statistics.

·       Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.

·       Experience working with large datasets.

Qualifications:

·       Bachelor’s degree in computer science, Data Analytics, Statistics, Mathematics, Business Analytics, Engineering, or a related field.

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