Extend (Australia) Pty Ltd

Lead Risk Analytics Data Scientist

Remote, US · Senior

Sponsorship not specified$125k-$155kDetected 36 days ago

StatisticsCustomer SupportActuarial ScienceUnderwriting

About the role

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.
A great opportunity to convert your analytics expertise into business impact by supporting measurement of unit economics to feed strong business decisions.
You also have the opportunity to take ownership of data architecture for the Risk Analytics function.

By integrating leading-edge technology with exceptional customer service, Extend empowers businesses to build trust and loyalty among consumers while reducing costs and increasing profits.
You'll design the premium structure from first principles, figure out how to validate it when the data is thin, and own it through launch.
Own the risk narrative with senior leadership.
Build the data foundation for Risk Analytics - and make it yours.
You'll design the data models, set the standards, and shape how this function works for the next several years.
If you've ever inherited an architecture you wished you could rebuild from scratch, this is the rare opportunity to build it right the first time.
You will collaborate with cross-functional teams to help Extend maintain a healthy loss ratio through premium changes, underwriting process and claims initiatives.
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.

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
Bachelor's degree in Actuarial Science, Mathematics, Statistics, or a related field

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

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.
$125,000 - $155,000 per year salaried*
Life at Extend:
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.
401(k) with Financial Guidance from Morgan Stanley.

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.
Today, Extend works with more than 1,000 leading merchant partners across industries, including fashion/apparel, cosmetics, furniture, jewelry, consumer electronics, auto parts, sports and fitness, and much more.

Extend is revolutionizing the post-purchase experience for retailers and their customers by providing merchants with AI-driven solutions that enhance customer satisfaction and drive revenue growth.
Our comprehensive platform offers automated customer service handling, seamless returns/exchange management, end-to-end automated fulfillment, and product protection and shipping protection alongside Extend's best-in-class fraud detection.
Extend is backed by some of the most prominent technology investors in the industry, and our headquarters is in downtown San Francisco.

This listing is sourced directly from Extend (Australia) Pty Ltd's careers page and normalized into a canonical job model.