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Senior Insurance Data Analytics Jobs in Exton, PA

TransUnion

Senior Data Analyst

Crum Lynne, PA

$90K - $150K/yr

  • Medical

  • Dental

  • Vision

  • PTO

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

  • Medical

  • Dental

  • Vision

  • PTO

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

Vanguard

Data Analyst, Specialist

Malvern, PA

Role Summary In this role, you will help turn data into decisions by combining strong technical ... from senior teammates and contribute to a growing, AI-native analytics community. Core ...

Jobot

Senior Insurance Defense Attorney

Philadelphia, PA · On-site

$130K - $160K/yr

  • Medical

  • Dental

  • Retirement

... a senior attorney to join its insurance defense practice in Philadelphia. This role is well-suited ... Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You ...

PMA Companies

Sr. Workforce Data Analyst

Blue Bell, PA · On-site

$82K - $103K/yr

The Sr Workforce Data Analyst will play a critical role in building and strengthening the ... As workforce analytics capabilities continue to expand, this position will help identify ...

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All JobsInsurance Data Analytics JobsSenior Insurance Data Analytics JobsSenior Insurance Data Analytics Jobs in Exton, PA

Senior Insurance Data Analytics information

See Exton, PA salary details

$16

$54

$78

How much do senior insurance data analytics jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for senior insurance data analytics in Exton, PA is $54.83, according to ZipRecruiter salary data. Most workers in this role earn between $45.00 and $64.95 per hour, depending on experience, location, and employer.

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 cities near Exton, PA are hiring for Senior Insurance Data Analytics jobs?

Cities near Exton, PA with the most Senior Insurance Data Analytics job openings:

Senior Insurance Data Analytics jobs near you

Data Science Senior Associate- Card Data & Analytics team

JPMorgan Chase & Co.

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 3 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

72nd of 171 rated banks

Job description


As a Data Science Senior Associate in the Card Data & Analytics team, you will develop AI/ML solutions that drive the bottom line for our Credit Card business. You will utilize your skills in data analytics, consulting, and programming to support strategic initiatives and deliver actionable insights. Collaborate with partners across the Card business to define problems, scope solutions, and deliver high-quality analytical models. Your work will involve a mix of consulting, data science, and programming, with a focus on driving data science and analytics strategies.
Job Responsibilities:
  • Leverage experience and analytical skills to uncover novel use cases of Big Data analytics, including opportunities to responsibly apply foundation models and Generative AI.
  • Drive data science and analytics strategies, including recommendations on analytical products and standards.
  • Help partners define business problems and scope analytical solutions.
  • Build an understanding of problem domains and available data assets.
  • Research, design, implement, and evaluate analytical approaches and models, including GenAI-based methods.
  • Perform exploratory statistics and data mining tasks on diverse datasets.
  • Communicate findings and obstacles to stakeholders to drive delivery to market.
  • Develop subject matter expertise in financial and operational domains.
  • Code solutions with strong programming skills.
  • Collaborate across teams to deliver the best solutions for clients.

Required Qualifications, Capabilities, and Skills:
  • Bachelor's degree in a relevant quantitative field and 3+ years of data analytics experience, or advanced degree and 2+ years of experience.
  • Exceptional analytical, quantitative, problem-solving, and communication skills.
  • Intellectual curiosity for solving business problems.
  • Leadership and collaboration skills.
  • Knowledge of statistical software (e.g., Python, R, SAS) and data querying languages (e.g., SQL).
  • Familiarity with GenAI and prompt engineering basics (prompt design, evaluation, guardrails).
  • Experience with modern analytics tools (e.g., SAS, SQL, Hive, Hadoop, Spark, Python, Tableau, Alteryx).
  • Ability to convey complex information to technical and non-technical audiences.

Preferred Qualifications, Capabilities, and Skills:
  • Experience with LLM-enabled applications such as retrieval-augmented generation, classification or extraction from unstructured text, or agent-like workflows; exposure to evaluation methods for LLM quality, cost, and latency.
  • Understanding of key drivers within the credit card P&L.
  • Financial services background preferred.
  • M.S. degree or equivalent.

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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