Manager, Risk Analytics

About the role

You'll join our centralized Risk, Analytics & Data Science team as a Manager, serving as the most senior technical voice in the Risk Analytics function and the leading member to help build the entire function and team. You'll have full ownership of the Risk Function of Extend: the pricing methodology we standardize on, the risk framework leadership uses to make portfolio decisions, and the technical bar for the function as a whole. This is a Manager-track role with responsibility for growing and building the team—setting standards, mentoring Lead and senior data scientists, and representing Risk Analytics in high-stakes merchant deals and program decisions. You'll be accountable not just for your own analyses but for the function's methodology being sound.

We've invested heavily in modern data infrastructure and AI tooling, and we want someone excited to use them. If you want the scope and influence of a manager with the hands-on depth of an individual contributor, this role is for you.

Responsibilities

• Set the pricing methodology, not just the price. Lead pricing initiatives and define how Extend prices—frameworks, validation standards, and guardrails that make every new-category premium defensible, especially when data is thin.
• Own the risk strategy conversation with senior leadership. Serve as the C-suite's counterpart on portfolio health, recommending which programs to reprice, renegotiate, or exit, and defending the trade-offs.
• Turn a monitoring function into a decision engine. Design decision systems for claims initiatives, premium adjustments, and program renegotiations, driving them from analysis to adopted business process.
• Architect the data foundation for Risk Analytics. Own the design of the Risk Analytics layer on top of our dbt and Snowflake infrastructure, including data models, standards, and roadmap.
• Raise the floor for the whole team. Mentor Lead and senior data scientists, review critical work, and drive AI-native ways of working to increase output, speed, and quality.

Requirements

• 8+ years of experience in actuarial pricing, predictive modeling, or other Risk Analytics-related areas, with a track record of owning methodology or strategy.
• Strong analytical and data skills spanning SQL, Python or R, pipeline development and data modeling (dbt, Snowflake), and visualization tools such as Tableau or Streamlit.
• Demonstrated experience mentoring senior analysts or data scientists and raising a team's technical bar without formal authority.
• Ability to dive deep into data and communicate insights to audiences of all backgrounds, including the C-suite and non-technical teams.
• Relevant Actuarial experience (such as Associate of the Casualty Actuarial Society (ACAS) or equivalent exam experience) preferred but not required.
• Excited and passionate about new AI tools (Claude, Gemini, etc.) and eager to learn how they can improve day-to-day efficiency.
• Bachelor's degree in Actuarial Science, Mathematics, Statistics, or a related field.
• Ability and interest in thinking beyond the insurance organization, considering challenges across teams, and prioritizing what’s best for the business holistically.
• Empathy, humility, and curiosity.

Benefits

• Competitive salary based on experience, with full medical, dental, and vision benefits.
• Stock in an early-stage startup growing quickly.
• Generous, flexible paid time off policy.
• 401(k) with financial guidance from Morgan Stanley.

Pay

Expected pay range: $160,000 - $180,000 per year (salaried). Individual salaries are determined based on job-related knowledge, skills, and experience.