Pricing Actuary​/Modeler, Commercial Lines

Description

The Global Risk Solutions (GRS) Capital & Analytics group is seeking a highly motivated individual to join its Insurance Risk Parameterization & Analytics team. This individual will contribute to a small team of modelers responsible for designing, developing, and implementing dynamic UW Risk modeling and analysis for the Global Risk Solutions organization. They will support UW Risk parameterization, modeling, and validation as well as wide-ranging uses of the models.

The successful candidate will have strong analytical abilities, enjoy developing statistical models and processes, working with large data sets, and diving deep into drivers of line of business dynamics. Global Risk Solutions is a leading provider of commercial, specialty insurance, and reinsurance products, delivering a wide array of innovative products, deep technical expertise, strong client engagement and market-leading performance worldwide.

The product lines include workers’ compensation, commercial multi-peril, surety bonds, crisis management, marine, terrorism, management liability, cyber liability, and energy.

• Parameterize UW Risk excluding natural catastrophe risk
• Build and maintain UW risk models and output exhibits
• Develop new solutions and improvements for statistical models and processes used to calculate these inputs
• Maintain clear and concise documentation of methods and activities
• Implement timely and practical solutions to complex problems
• Validate model parameterization and model function
• Collaborate with Underwriting and Actuarial to understand the business and guide development of Risk Analytic tools that accurately reflect the business
• Communicate processes and parameterization results to stakeholders outside of the team

• Bachelor’s degree or higher in Mathematics, Actuarial Science, Statistics, Finance, Economics, or similar required
• Minimum 5-7 years relevant experience required
• Very strong analytical skills with solid understanding of core casualty actuarial methods, techniques, and standards
• Expert in MS Excel and experience coding;
  Experience working with Visual Basic for Applications (VBA) and Capital modeling software, R, and Python preferred
• Experience with stochastic financial modeling and forecasting preferred
• Experience parameterizing reserve risk and UW risk preferred
• Comfort with solving new problems and generating ideas for improving existing processes
• Experience communicating analysis and technical concepts

• Competencies typically acquired through a Bachelor’s degree in a quantitative field
• Advanced degree (MBA) and/or professional qualification in one or more areas of risk management is preferred, and 8 to 10 years of relevant experience
• Additionally, excellent quantitative analysis and modeling skills are required, in addition to significant experience in an analytical capacity (financial analysis, product management, actuarial, underwriting, etc)
• Working knowledge of ERM-related regulatory frameworks (Solvency II, NAIC ORSA, Com Frame) is a plus
• Very strong understanding of the risk characteristics of insurance industry required
• Excellent understanding of basic financial concepts and metrics, including financial statement analysis required

The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role.

• California
• Los Angeles Incorporated
• Los Angeles Unincorporated
• Philadelphia
• San Francisco

Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.