Health Actuarial, Data Analyst

Position Summary

The Actuarial/Data Analyst is part of an internal resource team that develops models and analyzes health care data, including cost transparency data, across the book of business to identify cost, utilization, and population health trends. The role builds expertise in relevant data sources, methodologies, and analytical tools; interprets results; and translates findings into actionable insights and resources for actuarial consultants and other client-facing teams. The analyst collaborates with internal stakeholders and external vendor partners to strengthen the team’s data capabilities and support consistent, informed analysis.

Key Responsibilities

• Data Extraction and Management: Extract, validate, and manage large, complex datasets from internal and external sources for use in book-of-business analyses and model development.
• Health Care Cost Transparency: Analyze health care cost transparency data and support related tools; develop expertise in the data, methodologies, limitations, and applications; and serve as the primary resource for internal teams and liaison to the external vendor partner.
• Book-of-Business Analysis: Analyze health plan performance across the book of business, identifying and interpreting trends in medical and pharmacy costs, utilization patterns, and population health to support client-facing teams.
• Analytical Insights: Interpret data and model results to identify meaningful patterns, explain key cost and utilization drivers, and develop actionable insights for internal stakeholders.
• Stakeholder Collaboration: Partner with actuarial consultants, senior analysts, and other client-facing teams to understand business needs, define analytical approaches, and communicate findings that support client strategy and decision-making.
• Analytical Communication: Summarize methodologies, findings, and implications through reports, presentations, dashboards, and other resources designed for technical and nontechnical audiences.
• Quality Assurance: Ensure the accuracy, validity, and integrity of data and analytical outputs while meeting timelines and maintaining high-quality standards.
• Process Improvement: Identify and support opportunities to automate reporting and improve data collection, modeling, and analysis processes.
• Predictive Modeling: Develop models for emerging business needs and estimate cost and utilization changes across the book of business. Adapt models for client-specific applications as requested by client-facing teams.

Requirements

• Education and Experience: Bachelor’s degree in a quantitative field, such as Actuarial Science, Mathematics, Statistics, Data Science, or Health Informatics. A minimum of three years of data analytics experience in the health insurance industry is required.
• Microsoft Office: Advanced knowledge of Microsoft Office applications, particularly Excel, Word, and PowerPoint.
• Data and Programming: Proficiency in SQL for data extraction and manipulation; experience with statistical software or programming languages such as R or Python is preferred.
• Data Visualization: Experience with data visualization tools such as Power BI or Tableau.
• Health Insurance Knowledge: Familiarity with health insurance concepts, including plan designs, networks, cost-containment strategies, payment integrity programs, medical terminology, and health care billing codes.
• Analytical Skills: Excellent quantitative, analytical, and problem-solving skills, with demonstrated ability to compile, analyze, and interpret financial and health care data to support decision-making.
• Communication and Organization: Excellent communication, interpersonal, and organizational skills.
• Initiative: High degree of self-motivation and creative problem-solving ability.
• Collaboration: Ability to provide clear direction when appropriate, listen to others, and incorporate diverse ideas and perspectives.
• Ownership and Service: Demonstrated commitment to serving internal stakeholders and client-facing teams while taking ownership of work products.
• Decision-Making: Ability to make well-supported decisions and follow through on implementation.
• Travel: Ability to travel less than 10%25.