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Insurance Data Analytics Jobs in Atlanta, GA (NOW HIRING)

Understanding of Group Insurance data domains * Basic understanding of data concepts (databases ... Detail-oriented with good analytical thinking. * Good communicator - able to ask the right ...

Let's talk about the Role The Senior Manager, Data Analytics leads a team of analysts and analytics ... insurance, sleep care management, Health Savings Account (HSA), Flexible Spending Account (FSA ...

Let's talk about the Role The Senior Manager, Data Analytics leads a team of analysts and analytics ... insurance, sleep care management, Health Savings Account (HSA), Flexible Spending Account (FSA ...

Let's talk about the Role The Senior Manager, Data Analytics leads a team of analysts and analytics ... insurance, sleep care management, Health Savings Account (HSA), Flexible Spending Account (FSA ...

... analytics, and regulatory compliance across a complex, global insurance environment. This is a high-impact leadership role responsible for building modern, cloud-based data architectures ...

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... Insurance, Science - Utilizing Business Intelligence and Reporting Tools (BIRT) for data-driven ... analysis and interpretation - Engaging in stakeholder management and competitive advantage ...

Industry Experience in Credit Card, finance, or insurance * Experience in data analysis, warehousing, and reporting (3-5 years preferred) * Experience using BI tools (MS power BI a plus) for data ...

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Insurance Data Analytics information

See Atlanta, GA salary details

$23

$52

$90

How much do insurance data analytics jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for insurance data analytics in Atlanta, GA is $52.65, according to ZipRecruiter salary data. Most workers in this role earn between $42.31 and $59.66 per hour, depending on experience, location, and employer.

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 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.

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.

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.

What are the most commonly searched types of Insurance Data Analytics jobs in Atlanta, GA?

The most popular types of Insurance Data Analytics jobs in Atlanta, GA are:

What are popular job titles related to Insurance Data Analytics jobs in Atlanta, GA?

For Insurance Data Analytics jobs in Atlanta, GA, the most frequently searched job titles are:

Infographic showing various Insurance Data Analytics job openings in Atlanta, GA as of September 2026, with employment types broken down into 1% As Needed, 76% Full Time, 17% Part Time, and 6% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $109,507 per year, or $52.6 per hour.

Senior Director, Data Architecture

Atlanta, GA

$64.75 - $86.50/hr

Full-time

Re-posted 11 days ago


Key responsibilities

  • Define and execute the data architecture vision and strategic roadmap in alignment with enterprise data strategy.

  • Translate functional and technical requirements into scalable data architectures and guide solution delivery.

  • Develop and maintain standardized insurance data models, schemas, and pipelines to support operational, analytical, and regulatory needs.


Job description

Join Starr, a global leader in commercial insurance with over a century of expertise. We empower our employees to innovate, make impactful decisions, and build lasting client relationships worldwide. At Starr, you'll work in an entrepreneurial culture alongside accessible leaders, leveraging our financial strength and vast industry experience to deliver solutions for our clients, no matter how complex. Grow your career with a rapidly growing company that invests in its people and their ability to drive real progress.

Job Description: Senior Director, Data Architecture

Location:New York, NY

Reports to:Head of Data Engineering & Chief Data Officer

Department:Starr Technology Group

Overview:

The Senior Director, Data Architecture is a pivotal leadership role responsible for championing, building, and scaling a world-class Data Architecture practice in support of Starr's global enterprise data vision. Reporting to the Chief Data Officer, the candidate will define and deliver modern, resilient, and secure data architectures that underpin all insurance systems, capabilities, and platforms. Leveraging deep domain experience in insurance (P&C and Specialty lines), data management, modeling, and analytics, the Senior Director will translate business and technical requirements into scalable data solutions that enable the organization's innovation, regulatory compliance, and growth objectives.

Central to this role is the development and stewardship of data architectural best practices, reference architectures, and standardized frameworks that drive consistency, quality, and governance across all data assets-spanning domains from Customer, Policy, Claims, and Financials to the augmentation of external data. The Senior Director will work collaboratively with engineering, product, analytics, and delivery teams to translate requirements into solutions, providing architectural oversight and hands-on technical delivery for strategic initiatives, and maintaining a current/future state roadmap for all data capabilities.

This leader will drive adoption of modern data technologies, advanced data modeling, cloud architectures, and data governance principles, while building the discipline and maturity of Starr's Data Architecture organization. This position is critical for supporting the scalable growth of business intelligence, analytics, and cross-enterprise data operations across the insurance portfolio.

Responsibilities:

Data Architecture Vision, Strategy & Governance

  • Define and execute the data architecture vision and strategic roadmap in close alignment with the CDO and enterprise data strategy.
  • Architect scalable, resilient, and secure solutions for enterprise-wide data integration, warehousing, analytics, operational systems, and augmentation with external data sources.
  • Develop and champion standardized, insurance-centric data modeling frameworks, data architecture best practices, and reference architectures to ensure quality, consistency, and performance.

Architectural Oversight & Solution Delivery

  • Drive architectural oversight for design, build, and operate phases of critical enterprise data initiatives-including new insurance products, data platforms, modernization, digital transformation, and regulatory projects.
  • Translate functional and technical requirements into robust data architectures; guide engineering, analytics, product, and delivery teams throughout the data solution lifecycle.
  • Perform hands-on technical delivery and problem solving for complex, strategic initiatives, ensuring successful execution against business, compliance, and technical requirements.
  • Formalize current- and future-state architectural roadmaps that support unified, global, and consistent views of Customer, Policy, Claims, Financials, and other key insurance data domains.

Insurance Data Domain Leadership

  • Develop and maintain standardized insurance data models, schemas, and pipelines; ensure applicability across the business for operational, analytical, and regulatory purposes.
  • Integrate core insurance application data (e.g., Policy Administration, Claims, Reinsurance, Financials) with enterprise data platform and external third-party sources for holistic insights.
  • Lead data architecture initiatives supporting evolving requirements of actuarial, underwriting, claims, compliance, finance, and product innovation teams.

Adoption of Modern Data Technologies & Best Practices

  • Evaluate, select, and drive adoption of cutting-edge data technologies and architectural approaches (cloud-native, distributed, streaming, data lakehouse, real-time analytics).
  • Accelerate enablement of cloud-based, medallion architecture (bronze/silver/gold), data pipeline automation, metadata management, and advanced analytics infrastructure.
  • Promote strong data governance integration-including quality, cataloging, lineage, privacy, security, and compliance policies-across all data architecture outputs.

Data Organization Leadership & Team Building

  • Build and mentor a high-performing Data Architecture function, including data architects, modelers, solution designers, and technical delivery leads.
  • Foster cross-team collaboration with engineering, operations, analytics, and governance teams, ensuring seamless delivery of robust data solutions across the enterprise.

Stakeholder Engagement & Change Leadership

  • Serve as chief architectural advisor and liaison to internal and external stakeholders - educating teams on data architecture capabilities and value.
  • Ensure business requirements are accurately captured and reflected in scalable technical designs; drive business adoption and platform utilization.

Continuous Improvement, Innovation, & Risk Management

  • Champion continuous improvement in architectural processes, tooling, methodology, and capability development.
  • Lead architectural risk assessment, mitigation, and proactive controls to ensure technical, business, and compliance objectives are met.
  • Track and report architectural health and progress using enterprise KPIs, quality metrics, and roadmap milestones.

Technical Skills & Requirements:

  • Advanced hands-on expertise in designing and modeling enterprise data architectures (cloud-native, hybrid, lakehouse, distributed, real-time).
  • Deep experience with data management, advanced data modeling (conceptual, logical, physical), insurance data schemas, and master data/reference data frameworks.
  • Proven delivery across modern data technology stacks-Databricks, Snowflake, Spark, AWS/Azure/GCP data services, streaming/data integration platforms, metadata/cataloging tools.
  • Expertise in Medallion architecture, batch/streaming pipeline design, external data augmentation.
  • In-depth understanding of metadata management, data governance, lineage, cataloging, residency and security/privacy frameworks.
  • Familiarity with insurance business models, core platforms (Guidewire, Duck Creek, Majesco), and regulatory/compliance-driven architecture requirements.
  • Ability to assess legacy and modern architectures, and transition organizations toward future state aligned with business goals.
  • Experience driving transformation of architecture standards and best practices across globally distributed teams.

Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, Data Engineering, Information Systems, or related field; advanced degree highly preferred.
  • 12+ years' experience in data architecture, data modeling, and enterprise data management with 5+ years in senior leadership roles.
  • Significant insurance industry experience, ideally within P&C and Specialty, with deep understanding of industry data requirements.
  • Proven track record architecting, delivering, and governing complex data solutions for operational, analytical, and regulatory purposes in global organizations.
  • Expertise building and formalizing insurance data models, frameworks, and best practices.
  • Experience leading architectural teams, driving transformation and adoption of modern data architectures and governance.
  • Excellent technical leadership, stakeholder management, communication, and problem-solving skills.
  • Professional certifications in data architecture, cloud platforms (AWS, Azure, GCP), and insurance data management are highly desirable.

An estimated salary range for this role is $200,000-$275,000

Starr is an equal opportunity employer, which means we'll consider all suitably qualified applicants regardless of gender identity or expression, ethnic origin, nationality, religion or beliefs, age, sexual orientation, disability status or any other protected characteristic. We recruit and develop our people based on merit and we're committed to creating an inclusive environment for all employees. We offer first class training and development opportunities to all employees. Our aim is to grow our own talent and bring out the best in people.