Senior Reinsurance Actuary — AI Analytics Lead

Marsh; New York (NY); Hybrid; USD 115,000 - 210,000; Full time

Benefits offered by this job

Hybrid work

Professional development

Job summary

Marsh is seeking a Reinsurance Actuary on the Global Analytics team. You will serve as a key analytics partner to brokers and clients, building complex analyses on premiums, risk, and loss liabilities. This role emphasizes AI-enabled approaches, Databricks, and Python to improve speed and scalability.

The position offers a hybrid work model across multiple U.S. offices, requiring three days per week in the office.

Qualifications

• ACAS with 5–7 years in the industry.
• Bachelor’s degree in Actuarial Science, Economics, Math, Statistics, or related field.
• Pricing, valuation, and/or capital modeling experience.
• Strong skills in Microsoft Office suite.
• Visualization skills (Power BI, Tableau, or similar).
• Coding experience in Python, Alteryx, R, VBA, SQL; comfortable with Databricks.

Responsibilities

• Consult with brokers on client needs and advise on reinsurance programs based on risk tolerance and industry trends.
• Communicate strategically with brokers, reinsurers, and clients to drive usage of actuarial services.
• Implement complex models to assess risk and develop pricing and strategies for various exposures.
• Evaluate how reinsurance structures impact client earnings and capital position.
• Use AI-enabled approaches to streamline repeatable work while maintaining standards.

Skills

ACAS with 5–7 years

Communication skills

Problem solving

Team collaboration

Education

Bachelor's degree in Actuarial Science, Economics, Math, Statistics, or related field

Tools

Databricks

Python

SQL

R

Alteryx

VBA

Tableau

Power BI

Job description

Marsh is seeking a Reinsurance Actuary on the Global Analytics team. You will serve as a key analytics partner to brokers and clients, building complex analyses on premiums, risk, and loss liabilities. This role emphasizes AI-enabled approaches, Databricks, and Python to improve speed and scalability.

The position offers a hybrid work model across multiple U.S. offices, requiring three days per week in the office.