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Senior Insurance Data Analytics Jobs in Pennsylvania

... 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 ...

Sr. Data Analyst

Paoli, PA · On-site

$84K - $106K/yr

Role Overview The Senior Analyst, Office of the CEO is the analytical engine of the executive ... Contribute to the definition of Zeus's future analytics and reporting architecture as the ERP ...

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 ...

Sr. Data Analyst

Paoli, PA · On-site

$84K - $106K/yr

Role Overview The Senior Analyst, Office of the CEO is the analytical engine of the executive ... Contribute to the definition of Zeus's future analytics and reporting architecture as the ERP ...

PA · On-site

$90 - $130/hr

Role Overview The Senior Analyst, Office of the CEO is the analytical engine of the executive ... Contribute to the definition of Zeus's future analytics and reporting architecture as the ERP ...

Sr. Data Analyst

Paoli, PA · On-site

$84K - $106K/yr

Role Overview The Senior Analyst, Office of the CEO is the analytical engine of the executive ... Contribute to the definition of Zeus's future analytics and reporting architecture as the ERP ...

$75 - $95/hr

Senior Data Analyst - People Analytics Working Location: PENNSYLVANIA, CENTER VALLEY Workplace Flexibility: Hybrid (It is required to be on site in the Olympus Center Valley, PA office location two ...

PW Growth Strategy Analytics is growing! We're opening a new role to support some of the most ... senior leader stakeholders to implement. * Develops, owns and manages recurring analytic or ...

Showing results 41-60

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 Data Scientist, Analytics & Informatics

UPMC Enterprises

Pittsburgh, PA • On-site

Full-time

Posted 5 days ago


UPMC rating

7.0

Company rating: 7.0 out of 10

Based on 1,273 frontline employees who took The Breakroom Quiz

423rd of 898 rated healthcare providers


Job description

Purpose:
The Technology Solutions team offers technical and business services for UPMCE portfolio companies and investment partners creating innovative healthcare solutions to drive clinical and financial outcomes. We support all stages of a healthcare technology venture's lifecycle with strategic, implementation, and operational services. The Data Analytics and Informatics Service within the Technology Solutions team provides key data-driven insights for both Digital Solutions and Translational Sciences focus areas to address critical business questions supporting investment and product development life cycles. The Senior Data Scientist on the DAI team will lead the design, development, and deployment of complex analytical models supporting health outcomes research, product development, and strategic business initiatives. The Senior Data Scientist will collaborate closely with clinical faculty, subject matter experts, and business leaders to address pressing healthcare challenges, serving as a key technical expert and mentor for junior team members. This role draws heavily on advanced data science techniques, predictive modeling, and medical informatics, with an emphasis on delivering actionable insights and driving innovation.

Please note that this position is in-office 3 days per week.
Responsibilities:

  • Lead Complex Modeling & Research
    • Conceptualize and implement complex statistical and machine learning models to evaluate health outcomes, cost-effectiveness, and other critical business needs.
    • Collaborate with clinical faculty and subject matter experts to identify research hypotheses and conduct rigorous analyses using large real-world healthcare data sets.
  • Mentorship & Team Leadership
    • Provide guidance and mentorship to junior and mid-level Data Scientists, reviewing their work, offering technical support, and promoting best practices.
    • Facilitate knowledge-sharing sessions to encourage professional growth, foster collaboration, and maintain high-quality standards within the team.
  • Project & Stakeholder Management
    • Independently manage large-scale data science projects, including scoping, planning, execution, monitoring, and stakeholder communication.
    • Collaborate cross-functionally to align data-driven initiatives with strategic objectives, ensuring timely delivery of insights and solutions that address business challenges.
    • Serve as a trusted advisor by proactively identifying opportunities to apply advanced analytics for improved clinical and financial outcomes.
  • Data Extraction & Analysis
    • Review data extraction processes using electronic medical records (EMRs) and additional healthcare data sources to generate high-fidelity datasets for analysis.
    • Design and maintain end-to-end analytical pipelines, including pre-processing, validation, feature engineering, model development, and performance monitoring.
  • Advanced Analytics & Methodology
    • Apply observational study designs, advanced causal inference methods (e.g., propensity scores, handling missing data), and statistical techniques relevant to healthcare research.
    • Explore, evaluate, and integrate emerging technologies (e.g., AI/ML frameworks, cloud-based tools) to continuously improve modeling efficiency and scalability.
  • Communication & Knowledge Translation
    • Present findings through clear, compelling visualizations and narratives that resonate with both technical and non-technical audiences, including senior executives.
    • Contribute to manuscripts, abstracts, posters, and conference presentations, demonstrating the impact of advanced analytics in healthcare.
  • Continuous Improvement & Thought Leadership
    • Stay abreast of industry trends, research advances, and best practices in data science and healthcare analytics.
    • Proactively share insights and implement innovative analytics methods to maintain UPMCE's position as a thought and technical leader in the healthcare data science space.
  • Master's in health economics, data science, statistics, computer science or related field, with at least 5 years of experience in developing, implementing and overseeing models related to health services/ outcomes research and medical information programs or related work experience;
  • OR, PhD/MD with training or equivalent terminal degree in health economics, data science, statistics, computer science or related field, with at least 3 years of experience in developing, implementing and overseeing models related to health services/outcomes research and medical information programs or related work experience.
  • Comparable combination of education and experience will be considered in lieu of the above stated qualifications.
  • Demonstrated expertise in relevant applied analytical methods in healthcare (payor/provider).
  • Demonstrate prior independent application of data science methods specifically to healthcare industry data.
  • Ability to leverage cutting-edge data science experience from other industries (e.g., population segmentation, risk analysis, optimization analysis, real-time analytics) to advance healthcare analytics will be strongly considered in lieu of health care experience.
  • Advanced Analytics Skillset
    • Advanced proficiency in clinical and scientific research methodologies to generate research questions, query complex clinical data to conduct descriptive and predictive analysis that create new insights to address UPMCE's business needs.
    • Experience with cloud-based data platforms and tools (e.g., AWS, Azure, GCP) to build, deploy, and scale models.
    • Strong understanding of observational study designs, confounding control, and real-world data (RWD) analytics.
    • Familiarity with data visualization tools (e.g., Tableau, Power BI) for creating impactful reports.
  • Communication & Stakeholder interaction
    • Effective data analysis and interpretation skills with ability to draw and present quantitative conclusions leveraging graphs, and other visualizations to enable rapid understanding of clinical data to deliver business insights.
    • Excellent verbal and written communication skills to translate complex concepts into actionable insights for diverse stakeholders, including senior leadership and customers.
    • Ability to represent analytics methodologies, findings, and recommendations in cross-functional forums, influencing the team leadership's decision-making.
    • Exceptional interpersonal skills, and entrepreneurial orientation characterized by pragmatism, independence, self-determination, and an agile, flexible behavior style.
    • Excellent communicator with ability to prepare and deliver clear scientific and business communication materials (documents, presentations) for internal and external facing activities.
    • Ability to influence team leadership and customers through effective communication of data science methods and study results.
  • Business
    • Demonstrated understanding of the differences between business requirements, scientific rigor, and technical constraints with ability to distill complex issues and ideas down to simple comprehensible terms.
    • Demonstrated understanding of financial metrics and cost efficiencies that have a positive business impact.
  • Project Management
    • Proven track record of successfully leading and delivering large projects in fast-paced, matrixed environments.
    • Strong mentoring skills, with the ability to guide junior team members in adopting best practices and improving their technical capabilities.
    • Exceptional time management, organizational, and prioritization skills with experience in agile/scrum methodologies.
    • Self-driven, scientifically curious individual who thrives in a high pace, and rapidly evolving business environment that supports entrepreneurs and founders.
  • Preferred
    • Background in applying AI/ML to real-time analytics, optimization, or population health segmentation.
    • Experience with advanced analytics research infrastructure and platforms.
    • Previous publications or presentations at scientific conferences showcasing successful data science initiatives.

Licensure, Certifications, and Clearances:

  • Act 34


UPMC is an Equal Opportunity Employer/Disability/Veteran


What UPMC employees say

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Benefits

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About UPMC

Sourced by ZipRecruiter

UPMC, a distinguished healthcare provider and insurer headquartered in Pittsburgh, PA, operates with a $23 billion budget. With a vast team of 92,000 employees, including 4,900 physicians, UPMC serves through over 40 academic, community, and specialty hospitals, along with 800+ doctors' offices and outpatient sites. Committed to patient-centered care, UPMC pioneers innovative and cost-effective models of accountable healthcare. The organization maintains a close affiliation with the University of Pittsburgh, a top recipient of National Institutes of Health research funding since 1998.

Industry

Health care and social assistance

Company size

10,000+ Employees

Headquarters location

Pittsburgh, PA, US