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Senior Insurance Data Analytics Jobs in Pennsylvania

Data & Analytics Senior Analyst

Indiana, PA ยท 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 ...

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 ...

... with senior internal and client leaders while driving measurable outcomes . Key Responsibilities ... Data & Analytics Products (Build + Scale) โ€ข Own the end-to-end lifecycle of data and analytics ...

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 ...

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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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:

Sr. Analyst, Data & Analytics Engineering

Coraopolis, PA โ€ข On-site

$82K - $103K/yr

Full-time

Posted 13 days ago


Job description

Purpose:

The Sr. Analyst, Data & Analytics Engineering provides strategic and tactical support to Vanscoy Rare Pharmacy and will report directly to the Data Analytics Manager. The Sr. Analyst, Data & Analytics Engineering works directly with Vanscoy Rare Pharmacy teams to determine reporting requirements, develop data pipelines, and distribute reports on to internal and external stakeholders. As a Sr. Analyst, Data & Analytics Engineering, you will be responsible for designing, developing, and maintaining our data infrastructure, ensuring the efficient and secure processing of large volumes of data, and providing actionable insights through data visualization. You will serve as an organizational expert on data infrastructure by working closely with Vanscoy Rare Pharmacy leadership, determining the needs of the team, and providing knowledge and recommendations to support the data and analytics needs. This role is also responsible for identifying quality issues and implementing solutions to potential issues that may arise through data analysis and reporting. The Sr. Analyst will also be responsible for mentoring and coaching analysts, engineers, and other data team members. In some cases, the Sr. Analyst, Data & Analytics Engineering will be responsible for delegating work based on organizational priorities. 

The Sr. Analyst, Data & Analytics Engineering will also support the organization’s evolving AI and advanced analytics initiatives by helping evaluate opportunities for intelligent automation, anomaly detection, predictive analytics, workflow optimization, and AI-assisted reporting. AI-enabled capabilities should be implemented with appropriate governance, security, auditability, and human oversight to support operational and compliance objectives.

The Sr. Analyst, Data & Analytics Engineering will be responsible for promoting best practices in data engineering, reporting development, governance, and documentation. This role may also be responsible for prioritizing and delegating work based on organizational initiatives, project timelines, and operational priorities.


Responsibilities:

  • Design and Development: Assist with the design and development of scalable data pipelines using Azure Data Factory and Azure Synapse Analytics to support data integration, transformation, and loading processes.
  • Data Management: Oversee the management and optimization of data storage solutions, including data lakes and data warehouses, ensuring data is organized, accessible, and secure.
  • Data Delivery: Utilize data pipelines and triggers to create and deliver data files reliably and repeatably.
  • Data Visualization: Utilize Power BI to create and maintain reports and dashboards that provide actionable insights to stakeholders.
  • Collaboration: Work closely with pharmacists, business stakeholders, and Vanscoy Rare Solutions leadership to understand data requirements and deliver solutions that meet business needs.
  • Performance Optimization: Monitor and optimize the performance of data pipelines and storage solutions to ensure efficient data processing and retrieval.
  • Data Governance: Implement and enforce data governance policies and best practices to ensure data quality, consistency, and compliance with regulatory requirements.
  • Mentorship: Provide technical leadership and mentorship to junior data engineers, fostering a culture of continuous learning and improvement.
  • Innovation: Stay up-to-date with the latest industry trends and advancements in data engineering, Azure technologies, and data visualization tools, and apply this knowledge to drive innovation within the team.
  • Other duties as assigned 



Required Qualifications:

  • Education: Bachelor’s or Master’s degree or equivalent experience in Computer Science, Information Technology, and Data Analytics.
  • Experience: Minimum of 5 years of experience in data engineering, with a focus on using Microsoft Azure services and Power BI.
  • Technical Skills:
    • Proficiency in data modeling, ETL processes, and data warehousing concepts.
    • Proficiency in Azure Data Factory and Azure Synapse Analytics.
    • Strong knowledge of SQL and experience with database management systems.
    • Knowledge of Power BI for creating reports and dashboards.
    • Knowledge of programming languages such as Python, Scala, or Java.
  • Soft Skills:
    • Excellent problem-solving and analytical skills.
    • Strong communication and collaboration abilities.
    • Ability to lead and mentor junior data analysts and engineers.
    • Detail-oriented with a focus on data quality and accuracy.


Preferred Qualifications:

  • Experience with Snowflake a plus.
  • Experience with SSIS and Tableau or PowerBI a plus.
  • Certification in Microsoft Azure Data Engineering or related areas.
  • Experience in the healthcare or pharmaceutical industry.

Work Environment

Vanscoy Rare offers a hybrid work structure, combining remote work and in-office requirements. The frequency of onsite requirements will vary depending on role, operational needs, meetings, client visits, or team collaboration activities. Employees must be within commuting distance to Pittsburgh, PA, and able to report to the office when needed. We will provide advance notice when possible. This role routinely involves standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines. When telecommuting, employees must have reliable internet access to utilize required systems and software required for the position's responsibilities. The amount of time the employee is expected to work per day or pay period will not change while working from home. Employees are responsible for the set-up of their home office environment, including physical set-up, internet connection, phone line, electricity, lighting, comfortable temperature, furniture, etc. Employee’s teleworking space should be separate and distinct from their “home space” and allow for privacy.

 

Physical Demands


 While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to stand; walk; use hands and fingers, handle or feel; and reach with hands and arms.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential function of the job.