Commercial Lines Risk Modeler & Actuarial Analytics

Liberty Mutual Insurance; United States; Remote; USD 110,000 - 180,000; Full time

Job summary

Liberty Mutual Insurance is seeking a highly capable quantitative professional to join the Global Risk Solutions Capital & Analytics team. The role focuses on designing, developing, and implementing dynamic UW Risk parameterization, modeling, and analytics to drive risk insights for the Global Risk Solutions organization.

You will support model parameterization, modeling, and validation and work with large data sets to understand drivers of line-of-business dynamics.

Qualifications

• Bachelor’s degree in a quantitative field or higher
• 8–10 years of relevant experience preferred in risk/actuarial context
• Experience with ERM frameworks is a plus
• Strong analytical skills and ability to work with large data sets

Responsibilities

• Parameterize UW Risk excluding natural catastrophe risk
• Build and maintain UW risk models and outputs
• Develop new statistical models and processes
• Document methods clearly and concisely
• Provide timely, practical solutions to complex problems
• Validate model parameterization and function
• Collaborate with Underwriting and Actuarial to reflect business dynamics
• Communicate parameterization results to stakeholders

Skills

Mathematics

Actuarial Science

Statistics

Finance

Economics

Modeling Methods

Communication of Analysis

Education

Bachelor’s degree in Mathematics/Actuarial Science/Statistics/Finance/Economics

Advanced degree (MBA) and/or risk management qualification

Tools

VBA

Capital modeling software

R

Python

MS Excel

Job description

Liberty Mutual Insurance is seeking a highly capable quantitative professional to join the Global Risk Solutions Capital & Analytics team. The role focuses on designing, developing, and implementing dynamic UW Risk parameterization, modeling, and analytics to drive risk insights for the Global Risk Solutions organization.

You will support model parameterization, modeling, and validation and work with large data sets to understand drivers of line-of-business dynamics.