Actuarial Associate — VM-22 Modeling & ALM

The Standard; Hawaii; On-site; USD 95,000 - 139,000; Full time

Job summary

The Standard’s Individual Annuities division seeks an Actuarial Associate to support VM-22 implementation and AXIS modeling enhancements. You will develop models, data processes, and analytics, working with valuation, pricing, FP&A, and investment teams to ensure accurate and actionable results.

This role targets process-oriented individuals who enjoy solving problems and communicating results, with opportunities to contribute to governance and ALM initiatives within the team.

Qualifications

• Bachelor’s degree (or equivalent) in mathematics, actuarial science, business, or related field preferred.
• 3+ years hands-on actuarial experience.
• Prior modeling experience with GGY AXIS (preferred).
• Hands-on experience with Individual annuities (preferred).
• Asset modeling and ALM experience (preferred).
• Projection/valuation modeling experience (VM-20/VM-21) preferred.

Responsibilities

• Applies understanding of functional area to support AXIS model enhancements for VM-22 valuation.
• Support VM-22 model implementation, including structure, assumptions, runtime optimization.
• Develop understanding of VM-22 for governance needs (change management, controls, validation).
• Collaborate with valuation, pricing, FP&A, and investment management to ensure result usability.

Skills

Python

Actuarial analysis

Modeling experience

Education

Bachelor’s degree in mathematics/actuarial science

Tools

GGY AXIS

Job description

The Standard’s Individual Annuities division seeks an Actuarial Associate to support VM-22 implementation and AXIS modeling enhancements. You will develop models, data processes, and analytics, working with valuation, pricing, FP&A, and investment teams to ensure accurate and actionable results.

This role targets process-oriented individuals who enjoy solving problems and communicating results, with opportunities to contribute to governance and ALM initiatives within the team.