Lead Risk Analytics Data Scientist

Role Description

You'll join our centralized Risk, Analytics & Data Science team at Extend, where you'll play an essential role in the risk monitoring process for our product protection and shipping protection offerings. You will collaborate with cross-functional teams to help Extend maintain a healthy loss ratio through premium changes, underwriting process and claims initiatives.

A great opportunity to convert your analytics expertise into business impact by supporting measurement of unit economics to feed strong business decisions.

You will also be partnering with the cross-functional teams (Product / Program, Revenue / Sales, etc.) to develop appropriate premiums for new coverages and product categories. This isn't a "maintain the existing model" role. You'll be involved from the moment a new merchant deal is being negotiated, through program design, all the way to launch.

You also have the opportunity to take ownership of data architecture for the Risk Analytics function. We've invested heavily in modern data infrastructure and AI tooling, and we want someone who's excited to actually use them. If you enjoy autonomy and the freedom to build your own pricing infrastructure, you’ll thrive on our team.

If you enjoy working with data and analytical tools/models and have always wanted to get more involved on the business side — this role is for you.

What You Will Be Doing

• Price deals no one has priced before.
• Turn a monitoring function into a decision engine.
• Own the risk narrative with senior leadership.
• Build the data foundation for Risk Analytics — and make it yours.
• Actually use AI to change how the team works.

Qualifications

• 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.
• 5+ years of experience working on actuarial pricing, predictive modeling or other Risk Analytics related areas.
• Ability to dive deep into data and communicate insights to audiences of all backgrounds, especially to 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 that 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.

Expected Pay Range

$125,000 - $155,000 per year salaried*

* The target base salary range for this position is listed above. Individual salaries are determined based on a number of factors including, but not limited to, job-related knowledge, skills and experience.

Benefits

• Working with a great team from diverse backgrounds in a collaborative and supportive environment.
• Competitive salary based on experience, with full medical and dental & vision benefits.
• Stock in an early-stage startup growing quickly.
• Generous, flexible paid time off policy.
• 401(k) with Financial Guidance from Morgan Stanley.