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Associate In Insurance Data Analytics Jobs in Ohio

CYNET SYSTEMS

Data Engineer

Mason, OH · On-site

$52 - $57/hr

Experience in Healthcare / Insurance / Data Analytics platforms. * Exposure to real-time streaming frameworks (Kafka, Kinesis, etc.). * Experience in data governance and data quality frameworks.

AVI Foodsystems

Head of Data & Analytics

Akron, OH

Founded in 1960, AVI Foodsystems has evolved into one of the most respected and trusted food ... Health, dental, vision, and life insurance for full-time team members * 401(k) with generous ...

Belcan

Data Analyst

West Chester, OH

$35 - $38/hr

Act as functional lead for analytics tools in support of AEO initiatives * Lead projects of varying ... Associate or bachelor"s degree from an accredited university * 5+ years of experience in data ...

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Associate In Insurance Data Analytics information

What is an 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 the key skills and qualifications needed to thrive as an associate in insurance data analytics?

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 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.

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The top searched job categories for Associate In Insurance Data Analytics jobs in Ohio are:

What cities in Ohio are hiring for Associate In Insurance Data Analytics jobs?

Cities in Ohio 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 Ohio as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 89% In-person, and 11% Remote job distribution.

Data Scientist - Insurance & Financial Services

MDAEdge

Columbus, OH • On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary:
MDAEdge is a company specializing in data solutions, and they are seeking a Data Scientist with expertise in Insurance and Financial Services. The role involves designing data models, executing data analysis, and collaborating with stakeholders to align data solutions with business needs.
Responsibilities:
• Demonstrated experience working directly with stakeholders, business partners, SMEs, systems peers, and cross-functional teams to gather data requirements and design data models that align with business needs.
• Skilled in structured execution of data analysis, data profiling, and data mapping tasks.
• Ability to translate current and future business requirements into conceptual, logical, and physical data model designs.
• Proficient in using standard data modeling tools (e.g., Erwin, ER/Studio, Toad Data Modeler, PowerDesigner).
• Experienced in designing data models for various patterns (e.g., relational, dimensional, hybrid) supporting data warehouse, BI, and big data applications.
• Skilled in creating new data models and extending existing ones across multiple DBMS platforms (e.g., Oracle, SQL Server, DB2, Snowflake, Teradata, NoSQL).
• Strong understanding of complex data integration and ETL processes; able to explain these clearly to both technical and non-technical stakeholders.
• Demonstrated ability to identify and resolve data model performance issues to optimize database functionality and overall system performance.
• Experienced in documenting and communicating data model designs and standards to ensure understanding and adherence across the organization.
• Excellent communication skills, with the ability to collaborate effectively with individuals across all levels of business and technology functions.
• Fluency in Python, SQL, and Unix.
• High proficiency in writing complex SQL queries.
• Experience with version control of databases and metadata management tools (e.g., Git, Liquibase).
• Background in the Insurance and Financial domains is highly desirable.
• Experience working in Agile environments using Lean, Kanban, and Scrum practices.
Qualifications:
Required:
• Demonstrated experience working directly with stakeholders, business partners, SMEs, systems peers, and cross-functional teams to gather data requirements and design data models that align with business needs.
• Skilled in structured execution of data analysis, data profiling, and data mapping tasks.
• Ability to translate current and future business requirements into conceptual, logical, and physical data model designs.
• Proficient in using standard data modeling tools (e.g., Erwin, ER/Studio, Toad Data Modeler, PowerDesigner).
• Experienced in designing data models for various patterns (e.g., relational, dimensional, hybrid) supporting data warehouse, BI, and big data applications.
• Skilled in creating new data models and extending existing ones across multiple DBMS platforms (e.g., Oracle, SQL Server, DB2, Snowflake, Teradata, NoSQL).
• Strong understanding of complex data integration and ETL processes; able to explain these clearly to both technical and non-technical stakeholders.
• Demonstrated ability to identify and resolve data model performance issues to optimize database functionality and overall system performance.
• Experienced in documenting and communicating data model designs and standards to ensure understanding and adherence across the organization.
• Excellent communication skills, with the ability to collaborate effectively with individuals across all levels of business and technology functions.
• Fluency in Python, SQL, and Unix.
• High proficiency in writing complex SQL queries.
• Experience with version control of databases and metadata management tools (e.g., Git, Liquibase).
• Experience working in Agile environments using Lean, Kanban, and Scrum practices.
Preferred:
• Background in the Insurance and Financial domains is highly desirable.
• Domain experience in Insurance and Financial Services is highly preferred.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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