Health and Benefits Actuarial Summer Intern- Northeast market – College Program 2027

Company

Marsh

Description

We are seeking a talented individual to join Marsh’s (formerly Mercer) Health and Benefits Actuarial and Financial Group (AFG). This role will be based in Marsh’s northeast market. This is a hybrid role that has a requirement of working at least three days a week in the office. We plan to hire summer interns in New York, Connecticut and Philadelphia Note that Mercer has become Marsh. A new name. A wider network of expertise. The same leading solutions across health and benefits, investments and retirement, and workforce and rewards. Through Marsh’s Health practice, you will help employers navigate the increasingly complex world of employee benefits, people risk and employee benefit cost management. Predicting, monitoring and managing rising costs for employers is a key role of Marsh’s AFG. Learn in a supportive culture through real-world experience and valuable mentorship. Marsh’s 2,500+ US Health consultants deliver disciplined, consistent approaches to benchmarking, data analytics, financial management, marketing, compliance and communication. Our client focus, integrity, expertise, and innovation are why clients choose Marsh. We are committed to setting the industry standard for ethical and transparent business practices. To learn more about Marsh’s Health practice, please visit https://www.mercer.com/what-we-do/health-and-benefits.html

We will count on you to

Perform responsibilities comparable to full-time analysts with 1:1 support from experienced colleagues Complete comprehensive analysis of health care data using spreadsheet and database management software Assist in the development of client communications, proposals, reports, spreadsheets, and presentations Perform basic cost projections using client cost and enrollment data with Marsh’s valuation model Price medical & prescription drug plan designs using proprietary Marsh tools Assist in the development of customized pricing through alternate scenario modeling of pla