P&C Actuary

This role helps support Lockton’s goal of providing clear, actionable insights for our clients. These insights are used to facilitate informed decision-making and deliver improved outcomes. The role is responsible for creating tailored solutions for individual clients as well as enhancing the Analytics group’s brand, workflows, and capabilities.

Job Responsibilities:

• Collaborate with internal and external stakeholders to understand needs, identify opportunities, and develop strategic solutions to clients’ Property and Casualty challenges

• Work with various tools (Excel, VBA, Power BI, R, Python, SQL, etc.) to create sophisticated and scalable analytic tools and processes

• Leverage Lockton’s data to answer ad hoc questions for internal and external audiences

• Create materials and trainings to enhance internal understanding of Analytics’ capabilities and contribute to white papers / research articles to advance Lockton Analytics’ brand in the market

• Remain informed on industry developments and effectively communicate the implications both internally and externally

• Work with analysts and other stakeholders to identify new or improved analytic solutions that solve business needs

• Communicate and explain complex analytic concepts to clients and internal associates

• Work with developers to embed actuarial methodologies in new proprietary Lockton applications

• Compile, analyze, interpret, and present data trends to guide decision-making

• Prepare a variety of analytic outputs based on client or prospect data, including loss projection and stratification, collateral analysis, simulation models, predictive models, claim dashboards, and other ad hoc reports

• Quantitative mindset as evidenced by a Bachelor’s Degree in actuarial science, math, statistics, analytics, data science, computer science, finance, or other business-related degree

• Strong critical thinking and problem-solving skills

• Highly effective oral and written communication skills

• A strong desire to work collaboratively with others

• Proficiency with Microsoft Office products, particularly Excel

• Self-motivation – willingness to take initiative and ownership on projects

• ACAS or FCAS

• Prior experience with R, Python, and/or Power BI is preferred

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