Position Overview: The Lead Pricing Actuary will play a critical role in the development and implementation of pricing models for various insurance products. This individual will lead a team of actuaries and work closely with other departments to ensure that pricing strategies align with business goals and market trends. The ideal candidate will have deep expertise in actuarial science, a strong understanding of pricing models, and a passion for leveraging technology to innovate and optimize pricing strategies.
Key Responsibilities:
- Lead the design, development, and implementation of advanced pricing models for insurance products across various lines of business.
- Manage and mentor a team of actuaries, providing guidance on pricing strategies, model development, and technical best practices.
- Collaborate with cross-functional teams including product, data science, underwriting, and technology to ensure that pricing models align with business objectives and market conditions.
- Oversee the pricing review process, ensuring models are validated, tested, and updated in accordance with evolving data and market trends.
- Analyze and interpret complex data sets to identify pricing opportunities and risks, and provide actionable insights to senior leadership.
- Monitor performance of pricing strategies and adjust as needed to maintain competitiveness and profitability.
- Stay current with industry trends, regulatory changes, and technological advancements to continuously improve pricing strategies.
- Communicate pricing strategies and results clearly to stakeholders, including executives and non-technical teams.
Qualifications:
- FCAS (Fellow of the Casualty Actuarial Society) designation is required.
- 7+ years of experience in actuarial pricing, preferably within the insurance or insurtech industry.
- Proven experience in leading teams and managing projects.
- Expertise in pricing model development, statistical analysis, and data-driven decision-making.
- Strong proficiency in actuarial software and data analysis tools (e.g., R, Python, SAS, Excel).
- Experience with modern actuarial tools, machine learning, and predictive analytics is highly desirable.
