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Associate In Insurance Data Analytics Jobs in Northbrook, IL

Hudson Manpower

Senior Data Analytics Engineer

Chicago, IL · On-site

$40 - $50/hr

The ideal candidate will have strong expertise in SQL, Python, data modeling, BI tools, and modern analytics engineering practices. Responsibilities * Design and maintain analytics solutions across ...

1872 Consulting

Data Engineer

Chicago, IL

$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 ...

Steame LLC

Data Analytics Engineer - Chicago

Chicago, IL · On-site

$120K - $130K/yr

Our roots in NowPow-a nationally recognized social care referral platform that connected 13 million ... The Role As a Data Analytics Engineer at STEAMe, you will sit at the intersection of analytics ...

BMO U.S.

Data Analytics and Visualization

Chicago, IL · On-site

Selects, configures and implements analytics solutions for consistency and repeatability. • Researches and applies continuous improvement in data visualization by identifying trends and patterns to ...

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All JobsAssociate In Insurance Data Analytics JobsAssociate In Insurance Data Analytics Jobs in Northbrook, IL

Associate In Insurance Data Analytics information

See Northbrook, IL salary details

$3.3K

$6.4K

$9.1K

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

As of Jun 9, 2026, the average monthly pay for associate in insurance data analytics in Northbrook, IL is $6,384.92, according to ZipRecruiter salary data. Most workers in this role earn between $5,791.67 and $6,808.33 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.

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.

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 are popular job titles related to Associate In Insurance Data Analytics jobs in Northbrook, IL? For Associate In Insurance Data Analytics jobs in Northbrook, IL, the most frequently searched job titles are:
What job categories do people searching Associate In Insurance Data Analytics jobs in Northbrook, IL look for? The top searched job categories for Associate In Insurance Data Analytics jobs in Northbrook, IL are:
What cities near Northbrook, IL are hiring for Associate In Insurance Data Analytics jobs? Cities near Northbrook, IL with the most Associate In Insurance Data Analytics job openings:
Associate In Insurance Data Analytics jobs near you
Infographic showing various Associate In Insurance Data Analytics job openings in Northbrook, IL as of May 2026, with employment types broken down into 84% Full Time, 10% Part Time, and 6% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $76,619 per year, or $36.8 per hour.

Senior Data Analytics Engineer

Hudson Manpower

Chicago, IL • On-site

$40 - $50/hr

Contractor

Posted 6 days ago

Job description

Job Summary
We are seeking a Senior Data Analytics Engineer to design, build, and optimize analytics solutions that support business intelligence, reporting, and decision-making. The ideal candidate will have strong expertise in SQL, Python, data modeling, BI tools, and modern analytics engineering practices.
Responsibilities
  • Design and maintain analytics solutions across raw and semantic data layers.
  • Partner with business stakeholders to translate business requirements into data models, dashboards, and actionable insights.
  • Build and optimize SQL and Python-based data pipelines for analytics platforms.
  • Establish and promote analytics standards, governance, and best practices.
  • Enable self-service analytics using BI and data preparation tools.
  • Document, test, validate, and monitor data quality to ensure trust in reporting.
  • Collaborate with analysts and support ad-hoc analytical initiatives.
  • Contribute to cloud-based analytics and data engineering solutions.
  • Support analytics related to financial risk, trading, and operational reporting where applicable.

Required Qualifications
  • Bachelor's or Master's degree in a quantitative field or equivalent experience.
  • 3+ years of experience in Data Analytics, Analytics Engineering, BI, Data Engineering, Risk Analytics, or Software Development.
  • Strong SQL skills with experience writing complex analytical queries.
  • Proficiency in Python for data processing and pipeline development.
  • Experience with Tableau and Alteryx or comparable BI/Data Preparation tools.
  • Experience with Git, code versioning, pull requests, and modern development workflows.
  • Exposure to dbt and workflow orchestration tools such as Airflow, Dagster, or Prefect.
  • Experience with cloud platforms such as AWS, Azure, Databricks, or Snowflake.
  • Strong understanding of data modeling concepts including 3NF and Star Schema.
  • Knowledge of statistics and analytical methodologies.
  • Strong communication and stakeholder management skills.

Preferred Qualifications
  • Experience in Financial Services, Trading, Clearing, Risk Management, or Capital Markets.
  • Experience supporting enterprise-scale analytics environments.

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