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Insurance Data Analytics Jobs in Columbus, OH (NOW HIRING)

Insurance industry experience, including familiarity with data domains such as policy, claims, billing, underwriting, or risk. * Six or more years of experience in data architecture, analytics ...

This role focuses heavily on data engineering, dataset design, and analytical modeling support-serving as a critical bridge between raw insurance data and actionable pricing insights. The analyst ...

Analytics Analyst

Columbus, OH · On-site

$77K - $123K/yr

This role focuses heavily on data engineering, dataset design, and analytical modeling support-serving as a critical bridge between raw insurance data and actionable pricing insights. The analyst ...

... Insurance, Disability Insurance. Analyze data for the purpose of identifying data anomalies ... Experience with Oracle or Teradata database desired Prior experience in a data analytics role ...

Join Central Insurance as a Data Analyst where you will play a pivotal role in transforming data into meaningful insights that drive business decisions and regulatory reporting. In this role, you ...

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Insurance Data Analytics information

See Columbus, OH salary details

$23

$52

$91

How much do insurance data analytics jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for insurance data analytics in Columbus, OH is $52.88, according to ZipRecruiter salary data. Most workers in this role earn between $42.50 and $59.90 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in insurance data analytics?

To thrive in Insurance Data Analytics, you need a solid understanding of data analysis, statistics, and insurance industry concepts, usually supported by a degree in mathematics, statistics, finance, or a related field. Proficiency with analytical tools like SQL, Python, R, and data visualization platforms (such as Tableau or Power BI), as well as certifications like CPCU or advanced analytics credentials, are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts translate complex data into actionable business insights. These skills are crucial for driving informed decision-making, risk assessment, and operational improvements within insurance organizations.

What are the typical responsibilities of someone working in insurance data analytics?

Professionals in Insurance Data Analytics are responsible for collecting, cleaning, and analyzing large sets of insurance-related data to identify trends, assess risk, and inform business decisions. They commonly develop predictive models, generate reports, and provide actionable insights that help underwriting teams, actuarial staff, and business leaders optimize processes or pricing strategies. Day-to-day tasks may also include collaborating with IT and business units to define data requirements, presenting findings to non-technical stakeholders, and ensuring data integrity. This role often involves a mix of independent analysis and team-oriented projects, offering a dynamic and engaging work environment for problem solvers.

How is data analytics used in insurance?

In insurance, data analytics is used by professionals to assess risk, set premiums, detect fraud, and improve customer segmentation. Analysts utilize tools like statistical models and machine learning algorithms to interpret large datasets, enabling more accurate underwriting and claims management. Strong analytical skills and knowledge of data visualization are essential for effective decision-making in this field.

What does a data analyst do in insurance?

An insurance data analyst examines large datasets to identify trends, assess risk, and support decision-making processes within insurance companies. They use tools like Excel, SQL, and data visualization software to interpret claims, policy data, and customer information, helping improve underwriting, pricing, and fraud detection.

Is data analytics a high paying job?

Data analytics roles, including those in insurance data analytics, are generally considered well-paying compared to many other entry-level positions. Salaries vary based on experience, skills, and location, but professionals with expertise in tools like SQL, Python, or R often earn competitive wages and have strong job growth prospects.

How much does an insurance data analyst make?

The average salary for an insurance data analyst typically ranges from $60,000 to $90,000 annually, depending on experience, location, and industry. Professionals with advanced skills in data visualization, statistical analysis, and tools like SQL or Python may earn higher salaries, especially in larger organizations or metropolitan areas.

What is insurance data analytics?

An Insurance Data Analytics job involves analyzing large volumes of insurance-related data to identify trends, assess risks, detect fraud, and improve decision-making. Professionals in this field use statistical models, machine learning, and data visualization tools to extract insights that help insurers optimize pricing, enhance customer experience, and reduce losses. They work with claims data, policyholder information, and external data sources to drive business strategy. Strong analytical skills, proficiency in data tools like SQL, Python, or R, and knowledge of insurance principles are essential for success in this role.

What are the most commonly searched types of Insurance Data Analytics jobs in Columbus, OH? The most popular types of Insurance Data Analytics jobs in Columbus, OH are:
What job categories do people searching Insurance Data Analytics jobs in Columbus, OH look for? The top searched job categories for Insurance Data Analytics jobs in Columbus, OH are:
What cities near Columbus, OH are hiring for Insurance Data Analytics jobs? Cities near Columbus, OH with the most Insurance Data Analytics job openings:
Infographic showing various Insurance Data Analytics job openings in Columbus, OH as of July 2026, with employment types broken down into 95% Full Time, and 5% Part Time. Highlights an 83% In-person, 5% Hybrid, and 12% Remote job distribution, with an average salary of $109,990 per year, or $52.9 per hour.

Lead Data & Analytics Architect

Hylant

Columbus, OH • On-site

Full-time

Re-posted 10 days ago


Hylant rating

9.8

Company rating: 9.8 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

1st of 303 rated insurance


Job description

The Opportunity:

The Lead Data Architect exists to define, own, and evolve Hylant's enterprise application and information architecture. This role ensures that current data initiatives are intentionally designed to meet today's analytical needs while enabling future innovation through scalable, secure, and wellgoverned platforms. The position serves as a technical authority and strategic partner across data engineering, analytics, and business teams. This role will be measured by its contribution to business outcomes such as operational efficiency, adoption of self-service data products, and AI agent effectiveness.

In This Role You Will Execute On:

  • Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps).

  • Responsible for application architecture (platform, tools, technologies) and information architecture (data models, data flow, data structures and data access)

  • Translate business and analytical requirements into scalable, secure, and feasible data architecture designs that support both nearterm delivery and longterm innovation.

  • Guide requirements gathering, backlog shaping, and solution design to ensure initiatives align with established architectural standards and futurestate roadmaps.

  • Lead the design of analytical data models, including dimensional and star schema designs for curated, businessready data layers.

  • Design and oversee endtoend data pipelines, including sourcetotarget mappings, transformation logic, and serving strategies.

  • Establish architectural patterns and standards for data ingestion, transformation, storage, governance, and analytics consumption.

  • Establish and enforce data governance frameworks, standards, and policies to ensure data quality, security, and compliance.

  • Ensure the integrity, quality, and validation of data across the full lifecycle, from source systems through curated datasets and reporting layers.

  • Partner closely with data engineering and analytics teams to provide architectural guidance throughout delivery while remaining accountable for solution quality. Mentor and guide the lead data engineer.

  • Own the Data Strategy & Lifecycle Management, treating EDW domains as data products with SLAs, ownership, and lifecycle

  • Contribute to AI, Machine Learning, and Analytics Enablement Roadmap.

  • Responsible for overseeing, integrating, and optimizing AI agents in data pipelines and ensuring the right mix of human and AI involvement. Ensure responsible use of AI agents and automation in data integration, transformation, and delivery.

  • Understand and own relationships with external support providers and vendors as needed.

  • Evaluate and recommend platform capabilities and emerging technologies to continuously improve performance, scalability, and usability of the data ecosystem. Ensure solutions and system are scalable, re-usable, and cost optimized.

  • Perform other duties and special projects as requested.

In This Role You'll Need:

  • Prefer bachelor's degree in computer science, data science, engineering, or a related field, or equivalent practical experience.

  • Insurance industry experience, including familiarity with data domains such as policy, claims, billing, underwriting, or risk.

  • Six or more years of experience in data architecture, analytics architecture, or enterprise data platform design.

  • Demonstrated experience designing and delivering data platforms built on Azure based technologies as well as with multi-cloud or hybrid environments.

  • Hands on experience with DevOps (CI/CD process), event streaming and processing, AI/ML toolset, Azure Databricks, Microsoft Data Factory, Delta Lake, Unity Catalog, and Azure cloud services.

  • Strong experience designing analytical data models, including dimensional and star schema approaches.

  • Advanced SQL skills and working proficiency with PySpark for data transformation and modeling.

  • Experience designing and validating end-to-end data pipelines, including data quality and reconciliation processes.

  • Ability to clearly communicate complex technical concepts to both technical and non-technical audiences.

  • Experience managing a team and in establishing an Architecture Review Board, Design Reviews, and Data Standards and Conventions.

  • Must be willing and able to travel for in-person meetings at least on a quarterly basis

  • Ability and willingness to travel by car or airplane for meetings, conferences, or other business-related functions.

  • Must be legally authorized to work in the United States


Why Hylant?

A multi-year recipient of Best Places to Work in Insurance, Hylant is a full-service insurance brokerage with over 20 offices in eight states. And since the founding of our family-owned business over 90 years ago, we made a promise to strengthen and protect the businesses, employees and communities of our client family by embracing them as our own. We're more than an insurance brokerage firm and you're more than a client, employee or neighbor. You're family. And that's just the way we treat you.

Hylant is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, marital status, sex, age, color, religion, national origin, Veteran status, disability or any other characteristic protected by law. If you have a disability or special need that requires accommodation, please let us know. Hylant participates in E-Verify.


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