Job Summary:
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:
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%.
