About Extend 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. About the Role We’re looking for a Senior Data Scientist to join the Revenue & Risk Analytics team. You’re experienced at developing strategic recommendations grounded in data to scale, drive, and recover revenue. Technical expertise is just the table-stakes; business and strategic thinking takes you to the next level: you know which questions are worth asking, how each answer drives business impact, and how the answers change what the company does next. This is a highly versatile role. One quarter, you might be designing a custom program end to end, from how to reserve for risk, price to customers, and tell that story to client-facing teams. The next, you might be identifying opportunities to improve coverage accuracy for risk mitigation, then work hand in hand with Product and Engineering to turn them into features. Your work will show up and contribute directly to our bottom line. What You Will Be Doing - Revenue optimization and risk mitigation: Own and identify innovative new strategies across the entire revenue waterfall to grow and recover revenue together with client-facing teams. - Storytelling for client-facing teams: Build talk tracks and narratives for Revenue to continuously optimize and grow existing partnerships, backed by data insights from testing, Monte Carlo simulations, and/or ML models.
- Influence the product roadmap: Test optimization ideas, prove they work with data, and make the case to backend Product and Engineering teams to turn them into features that change how the company makes money. - Data Infrastructure: Own, refine, and improve existing data pipelines to harness the power of data analytics, defining data structures, and leveraging advanced tracking methodologies to uncover revenue opportunities. - Role Model: Set the standard for the team in terms of analytical thinking and excellence. What We’re Looking For - 5+ years in product data science or consulting with a strong emphasis in strategic thinking and a track record of driving business impact. - Solid statistical foundations: experimentation, causal inference, forecasting, and modeling. - Previous experience working with backend Product and Engineering teams on implementing product roadmaps. - Expert knowledge of SQL, Python, A/B testing, and Github, with hands-on Snowflake and dbt (or close equivalents). - Intellectually curious, willing to think beyond just the revenue organization and prioritize what is best for the business holistically. - Empathetic, humble, and collaborative, with comfort in ambiguity and high ownership in a remote-first team. - Excited about AI tools (Claude, Gemini, etc. ) and eager to use them to complement your workflow. - Advanced degree in data science, analytics, economics, statistics or similar quantitative field. Expected Pay Range: $125,000 - $145,000 per year salaried* * The target base salary range for this position is listed above.
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