Manager, Risk Analytics & Data Science

About the Role:

You'll join our centralized Risk, Analytics & Data Science team as a Manager, to serve as the most senior technical voice in the Risk Analytics function as well as the leading member to help build the entire function / 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. You will be responsible for growing and building the team — setting standards, mentoring Lead and senior data scientists, and representing Risk Analytics in rooms where the biggest merchant deals and program decisions get made. You'll be accountable not just for your own analyses being right, but for the function's methodology being sound.

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

What You Will Be Doing:

As the technical leader as well as a people manager, you will

• Set the pricing methodology, not just the price. Pricing the risk premium accurately is essential for Extend’s economics. You'll not only lead the pricing initiatives but also define how Extend prices — the 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. You'll be the C-suite's counterpart on portfolio health: not just explaining why the loss ratio moved, but recommending which programs to reprice, renegotiate, or exit — and defending the trade-offs. Your recommendations move real dollars.
• Turn a monitoring function into a decision engine. We know what our loss ratios are. You'll design the decision systems — which claims initiatives to pursue, which premiums to adjust, which programs to renegotiate — and drive them from analysis to adopted business process.
• Architect the data foundation for Risk Analytics. We have dbt and Snowflake. You'll own the design of the Risk Analytics layer on top of it: the data models, the standards, and the roadmap that shapes how this function works for the next several years — and you'll bring the team along on it.
• Raise the floor for the whole team. Mentor Lead and senior data scientists, review the work that matters most, and drive AI-native ways of working so the entire function produces more, faster, at a higher standard. You'll have latitude to experiment and the expectation that you will.

What We're Looking For:

• 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 teams with less data & analytics experience
• Relevant Actuarial experience (such as Associate of the Casualty Actuarial Society (ACAS) or equivalent exam experience) preferred but not required
• Excited and passionate about the new AI tools (Claude, Gemini, etc.) and eager to learn how they can help improve our 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 the challenges of other teams, and prioritizing what is best for the business holistically, is essential
• Empathy, humility, and curiosity