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Senior Insurance Data Analytics Jobs in Pennsylvania

Galent

Client Engagement Manager

Erie, PA · On-site

We''re looking for a senior Insurance Data & AI leader to drive client engagements and lead enterprise data transformation initiatives. Key Requirements: * 10+ years of Data & Analytics consulting ...

S and T Bank

Data & Analytics Senior Analyst

Indiana, PA · On-site

$48K - $115K/yr

The Data & Analytics Senior Analyst works at the direction of a Team Leader to fulfill the data and analytical needs of their designated business partners. Delivers solutions including reporting ...

IQVIA

Associate Director, Data Analytics

Wayne, PA · Remote

The Associate Director of Data Analytics provides technical and people leadership to design, build ... Build and maintain senior client relationships; identify expansion opportunities and translate them ...

New

Transunion

Senior Data Analyst

Crum Lynne, PA

$90K - $150K/yr

As part of the Data Analytics Team, you will help with development of TransUnion's IP Geolocation ... You can also opt into alegal plan,pet insurance, andtravel accident coverage. For Your Family

TransUnion

Senior Data Analyst

Crum Lynne, PA

$90K - $150K/yr

As part of the Data Analytics Team, you will help with development of TransUnion's IP Geolocation ... You can also opt into alegal plan,pet insurance, andtravel accident coverage. For Your Family

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All JobsInsurance Data Analytics JobsSenior Insurance Data Analytics JobsSenior Insurance Data Analytics Jobs in Pennsylvania

Senior Insurance Data Analytics information

What does a senior insurance data analytics professional do?

A Senior Insurance Data Analytics professional analyzes large datasets to help insurance companies make informed decisions about risk, pricing, claims, and customer behavior. They use statistical methods, data modeling, and business intelligence tools to uncover trends and insights that can improve operational efficiency and profitability. In addition to interpreting complex data, they often collaborate with other departments to develop data-driven strategies and may oversee or mentor junior analysts within the team.

What are the key skills and qualifications needed to thrive as a senior insurance data analytics professional?

To thrive as a Senior Insurance Data Analytics professional, you need a strong background in statistics, data analysis, and domain knowledge of insurance, often supported by a degree in mathematics, statistics, or a related field. Expertise in data analytics tools such as SQL, Python, R, and experience with business intelligence platforms like Tableau or Power BI are typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex insights clearly set top performers apart in this role. These skills are crucial for driving data-driven decision-making, identifying business opportunities, and improving risk assessment and operational efficiency within insurance organizations.

What are some common challenges faced by senior insurance data analytics professionals when working with large and complex datasets?

Senior Insurance Data Analytics professionals often encounter challenges such as integrating data from multiple legacy systems, ensuring data quality and accuracy, and managing sensitive information in compliance with regulations. Additionally, translating complex analytical findings into actionable insights for non-technical stakeholders can be demanding. Overcoming these challenges requires strong technical skills, clear communication, and close collaboration with IT, underwriting, and actuarial teams.

What is the difference between Senior Insurance Data Analytics vs Insurance Data Analyst?

AspectSenior Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often with experience in insurance analyticsBachelor's in related field; entry to mid-level experience
Work EnvironmentSenior roles often involve leadership, project management, and strategic planning within insurance companiesFocus on data collection, analysis, and reporting under supervision or team guidance
Employer & Industry UsageUsed across insurance firms, especially in analytics, underwriting, and actuarial departmentsCommonly employed in insurance companies, focusing on data processing and reporting

Senior Insurance Data Analytics professionals typically have more experience, advanced skills, and leadership responsibilities compared to Insurance Data Analysts. While both roles require strong analytical skills and familiarity with insurance data, seniors often oversee projects, develop strategies, and mentor junior staff, whereas analysts focus on data analysis and reporting tasks.

What are the most commonly searched types of Insurance Data Analytics jobs in Pennsylvania?

The most popular types of Insurance Data Analytics jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Senior Insurance Data Analytics jobs?

Cities in Pennsylvania with the most Senior Insurance Data Analytics job openings:

Senior Insurance Data Analytics jobs near you

Client Engagement Manager

Galent

Erie, PA • On-site

Other

Re-posted 12 hours ago

Job description

We''re looking for a senior Insurance Data & AI leader to drive client engagements and lead enterprise data transformation initiatives.

Key Requirements:

  • 10+ years of Data & Analytics consulting experience
  • Strong Insurance domain experience (mandatory)
  • Expertise in AI/GenAI, Data Analytics, and Data Strategy
  • Experience with AWS, cloud data platforms, and modern data architecture
  • Strong client-facing consulting, executive stakeholder management, and solutioning experience
  • Experience leading large transformation programs, RFPs, and delivery governance

If you have a strong background in Insurance + Analytics + AI + Client Engagement, I''d love to connect and discuss this opportunity.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law 

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