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Extend, Inc. is seeking a Senior Data Scientist for Revenue Analytics to lead cross-functional initiatives that optimize revenue, build data-driven strategies, and embed AI into analytics workflows.
This fully remote role is within the continental US, enabling collaboration across Sales, Growth, Product, Engineering and Risk to drive measurable business impact. The ideal candidate has 5+ years in data science or consulting, expert SQL and Python skills, strong communication, and an advanced
Remote, US
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. 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.
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 backed by some of the most prominent technology investors in the industry, and our headquarters is in downtown San Francisco.
The Revenue Analytics team is focused on developing strategic recommendations grounded in data to scale, drive, and recover revenue. We are experts at synthesizing different contexts from Sales, Growth, Product, Engineering, and Risk to identify growth and expansion opportunities that directly drive the company’s bottom line. If you have a passion for breaking down complexity and ambiguity into quantifiable impact, you’ll thrive on our team.
$125,000 - $135,000 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.