SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 125,000 - 145,000 / annual
Extend is a B2B SaaS platform revolutionizing the post-purchase experience for retailers through AI-driven solutions. The company provides merchants with automated customer service, returns/exchange management, fulfillment automation, product protection, shipping protection, and fraud detection. Extend works with over 1,000 merchant partners across fashion, cosmetics, furniture, jewelry, electronics, auto parts, and sports industries, and is backed by prominent technology investors with headquarters in San Francisco.
You will join the Revenue & Risk Analytics team as a Senior Data Scientist, owning strategic data initiatives that directly impact the company's bottom line. This is a highly versatile role spanning multiple quarters of work: designing custom programs end-to-end (risk reserving, customer pricing, client narratives), identifying opportunities to improve coverage accuracy for risk mitigation, and collaborating with Product and Engineering to turn insights into features.
Key responsibilities include:
- Revenue optimization and risk mitigation: Identify and own innovative strategies across the revenue waterfall to grow and recover revenue in partnership with client-facing teams.
- Storytelling and client enablement: Build data-backed talk tracks and narratives for the Revenue team using testing results, Monte Carlo simulations, and ML models to optimize and grow existing partnerships.
- Product roadmap influence: Test optimization ideas, validate with data, and make the business case to backend teams to implement features that change revenue generation.
- Data infrastructure: Own, refine, and improve data pipelines, define data structures, and leverage advanced tracking methodologies to uncover revenue opportunities.
- Team leadership: Set the standard for analytical thinking and excellence within the team.
Requirements:
- 5+ years in product data science or consulting with strong emphasis on strategic thinking and proven track record of driving business impact.
- Solid statistical foundations in experimentation, causal inference, forecasting, and modeling.
- Previous experience collaborating with backend Product and Engineering teams on product roadmap implementation.
- Expert proficiency in SQL, Python, A/B testing, and Github; hands-on experience with Snowflake and dbt (or equivalents).
- Advanced degree in data science, analytics, economics, statistics, or similar quantitative field.
- Intellectually curious with ability to think beyond revenue organization and prioritize holistic business impact.
- Empathetic, humble, and collaborative; comfortable with ambiguity and high ownership in remote-first environment.
- Familiarity with AI tools (Claude, Gemini, etc.) and willingness to integrate them into workflow.
