Actuarial Intern: Data Modeling & Analytics

nationallifeinsurancecompany; Addison (TX); On-site; USD 26,000 - 39,000; Full time

Benefits offered by this job

Mentorship program

Networking opportunities

Job summary

National Life Group offers a 10-week paid internship exposing students to critical actuarial and data analytics work. Interns are paired with mentors and leaders, with an onsite schedule requiring four in-office days per week (Mon–Thu).

The program emphasizes real-world assignments, reporting, and collaboration across departments. Candidates are pursuing actuarial science or related degrees, with SOA exam progress and strong math/analytical skills.

Qualifications

• Pursuing a Bachelor’s Degree in Actuarial Science, Mathematics, Statistics, or related field
• Preferably a Junior in College - Expected Graduation May 2026
• Passing score on at least 1 SOA actuarial exam
• Strong mathematical and analytical aptitude; ability to work accurately and timely
• Proficiency in Microsoft Office Suite (Word, Excel, Outlook, PowerPoint)
• Experience with database software (SQL Server and/or Access)

Responsibilities

• Update actuarial models for product development or valuation work
• Perform queries in SQL or build macros in Excel to manipulate data
• Learn and leverage data analytics tools (Alteryx and Tableau) to investigate trends and summarize findings
• Run reports, analyze trends, and detect patterns in results

Skills

Strong mathematical aptitude

Analytical thinking

Team collaboration

Education

Bachelor’s degree in Actuarial Science/Math/Statistics or related field

Tools

SQL Server

Microsoft Excel

Access

PowerPoint

Job description

National Life Group offers a 10-week paid internship exposing students to critical actuarial and data analytics work. Interns are paired with mentors and leaders, with an onsite schedule requiring four in-office days per week (Mon–Thu).

The program emphasizes real-world assignments, reporting, and collaboration across departments. Candidates are pursuing actuarial science or related degrees, with SOA exam progress and strong math/analytical skills.