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Associate In Insurance Data Analytics Jobs in Chicago, IL

In this role, you will develop and execute a comprehensive data and analytics strategy, lead data ... Life insurance * 401(k) retirement plan with company match * Paid holidays and vacation * Short ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

... Associate, Certified Associate in Python programing (PCAP), Apache Spark certification will be given preference. * 1-2 years of programming in the field of data engineering, analytics, data ...

Job Summary Lead enterprise data and analytics teams in this pivotal role driving data-driven ... Our benefit package includes health insurance, life and disability, 401(k) contributions, paid time ...

New

Job Summary Lead enterprise data and analytics teams in this pivotal role driving data-driven ... Our benefit package includes health insurance, life and disability, 401(k) contributions, paid time ...

New

Data Analyst

Chicago, IL · On-site +1

$95K - $110K/yr

... years of experience in a data analytics role, ideally within financial services or wealth ... Perks & Benefits • 401(k) with Employer Match • Health Insurance (with HSA option) • Dental ...

Data Analyst

Chicago, IL · On-site

$95K - $110K/yr

... years of experience in a data analytics role, ideally within financial services or wealth ... Perks & Benefits • 401(k) with Employer Match • Health Insurance (with HSA option) • Dental ...

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Associate In Insurance Data Analytics information

See Chicago, IL salary details

$3.3K

$6.5K

$9.3K

How much do associate in insurance data analytics jobs pay per month?

As of Jun 25, 2026, the average monthly pay for associate in insurance data analytics in Chicago, IL is $6,480.25, according to ZipRecruiter salary data. Most workers in this role earn between $5,883.33 and $6,908.33 per month, depending on experience, location, and employer.

What are some common challenges faced by an Associate in Insurance Data Analytics, and how can they be addressed?

Associates in Insurance Data Analytics often encounter challenges such as working with large, complex datasets and ensuring data accuracy for reliable analysis. Additionally, interpreting data in the context of insurance policies and risk models requires both technical and industry-specific knowledge. Collaborating closely with underwriters, actuaries, and claims teams can help bridge knowledge gaps and enhance data-driven decision-making. Staying up-to-date with analytical tools and best practices can also help overcome these challenges and support career growth.

What is the difference between Associate In Insurance Data Analytics vs Insurance Data Analyst?

AspectAssociate In Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's degree in data science, statistics, or related field; certifications like CAP or CPCU beneficialBachelor's degree in data analysis, statistics, or related field; certifications like CAP or CPCU beneficial
Work EnvironmentEntry-level role in insurance companies or consulting firms, focusing on data collection and basic analysisMid-level role in insurance companies, analyzing data to support underwriting, claims, and risk assessment
Employer & Industry UsageCommonly used in insurance firms, agencies, and consulting firms for data support rolesUsed within insurance companies for data-driven decision making and reporting

The Associate In Insurance Data Analytics and Insurance Data Analyst roles share similar educational backgrounds and industry usage. However, the Associate role is typically entry-level, focusing on data collection and basic analysis, while the Insurance Data Analyst often has more experience and handles more complex data analysis tasks to support business decisions.

How much does a data analyst make at World insurance Associates?

A data analyst at World Insurance Associates typically earns between $55,000 and $75,000 annually, depending on experience and location. The role often requires proficiency in data analysis tools like Excel, SQL, or Tableau and may involve working with insurance data to support business decisions.

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

To thrive as an Associate in Insurance Data Analytics, you need strong analytical skills, proficiency in statistics, and a background in insurance or finance, often supported by a relevant degree. Familiarity with data analysis tools like SQL, Python, R, and insurance-specific platforms or certifications such as the CPCU or AIDA is highly valued. Attention to detail, problem-solving abilities, and effective communication are critical soft skills for interpreting data and conveying insights to stakeholders. These skills are essential for transforming complex insurance data into actionable strategies that drive business decisions and risk management.

Is AI replacing data analysts?

For an Associate in Insurance Data Analytics, AI tools are increasingly used to automate routine data processing and analysis tasks, enhancing efficiency. However, AI does not replace the need for skilled analysts who interpret insights, make strategic decisions, and ensure data quality, making human expertise essential in the role.

What are Associate In Insurance Data Analytics?

An Associate in Insurance Data Analytics is a professional who specializes in analyzing data within the insurance industry to help companies make informed decisions. They use statistical methods, data modeling, and business intelligence tools to derive insights about risk, customer behavior, and market trends. This role often requires knowledge of insurance processes, as well as technical skills in data analysis and interpretation. They play a key part in helping insurers optimize underwriting, pricing, claims, and customer experience.

What can you do with an associate's in data analytics?

An associate's in data analytics prepares individuals for roles such as data analyst or insurance data analyst, where they interpret data, create reports, and support decision-making processes. These roles often involve using tools like Excel, SQL, or data visualization software and may require understanding insurance industry data and analytics techniques.

What does a data analyst do at an insurance company?

A data analyst in an insurance company collects, processes, and analyzes data related to policies, claims, and customer behavior to identify trends and support decision-making. They often use tools like Excel, SQL, and data visualization software to create reports and improve risk assessment, pricing, and fraud detection processes.
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Sr. Manager- Data Analytics

Sr. Manager- Data Analytics

Excel Talent Solutions

Chicago, IL • Hybrid

Full-time

Posted 6 days ago


Job description

Sr Manager, Data Analytics & Solutions– Chicago (North – Hybrid, 3x week)
Overview
Our client has their global headquarters in the Chicago area and is a global consumer packaged goods organization that produces household staples that have been trusted for generations. As a result of their continued growth and expansion of their IT team, they established a need to bring a Sr Manager of Data Analytics and Solutions to drive a top corporate initiative to leverage AI/ML capabilities to improve accessibility of data inventory for analytics.
The keys to this role include:
  • Deep understanding and capability of optimizing the AI/ML capabilities of SAP as well as data architecture
  • Strong business acumen and can partner with functional leaders in supply chain, finance, sales, procurement, and manufacturing.
  • Previous experience working in a CPG manufacturing environment.

Their Spec:
This is a high-impact role focused on leading the development of data products that unlock insights and empower decision-making across various functions such as Supply Chain, Manufacturing, Finance, Sales, Trade and Procurement. We’re seeking a techno-functional leader who is passionate about innovation and committed to delivering impactful solutions to our internal customers. You will also be supported by a Data & Analytics Shared Services Center of Excellence (COE) for advanced data modeling and visualization. The ideal candidate brings deep experience with analytics best practices from mature data environments and thrives in agile, fast-evolving settings—skilled in both strategic leadership and hands-on execution
  • Manage the end-to-end lifecycle of data products, including stakeholder engagement, design, deployment, and sunsetting of legacy solutions.
  • Deliver impactful data solutions that support strategic decisions across various functions within our organization.
  • Act as a trusted advisor, bridging the gap between business needs and technical execution within cross-functional teams.
  • Promote data literacy by training functional partners and enabling self-service analytics adoption.
  • Influence enterprise data management and architecture by identifying capabilities that drive business value.
  • Lead the design, development, and ongoing management of data and decision-support products—such as dashboards, reports, and analytical queries.
  • Serve as the main liaison for business stakeholders in these areas, ensuring their needs are translated into scalable data solutions.

What they are seeking:
  • BA/BS degree in information technology, Computer Science, Data Science, or a related field for data and analytics along with 7+ years of professional experience in Data & Analytics roles, with a strong record of delivering impactful data solutions
  • AI/ML Operationalization: Skilled in deploying and scaling AI/ML models beyond experimentation to deliver business impact in production environments.
  • Proven expertise in designing and deploying end-to-end data products across Supply Chain, Manufacturing, Finance, Sales, Trade and Procurement domains, preferably within the Consumer-Packaged Goods (CPG) industry
  • Minimum 5 years of experience working with SAP data products (e.g., BW, HANA, Datasphere, Databricks, ECC, S/4HANA), with deep understanding of SAP data architecture in CPG company
  • Hands-on experience with visualization and reporting tools such as SAP Analytics Cloud, Power BI, Business Objects, and Analysis for Office
  • Effectively bridges technical and commercial teams by simplifying complex data into clear, actionable insights aligned with strategic goals.