Senior Data Scientist, Revenue & Risk Analytics
About The Position
Extend is seeking a Senior Data Scientist to join its Revenue & Risk Analytics team and develop strategic, data-grounded recommendations to scale, drive, and recover revenue. The role combines technical data science with business and strategic thinking, including identifying valuable questions, assessing their business impact, and translating results into company decisions. The work directly contributes to Extend’s bottom line and varies across initiatives, such as designing programs that account for risk and pricing, improving coverage accuracy, and partnering with Product and Engineering to implement successful ideas. Extend provides AI-driven post-purchase solutions for retailers, including automated customer service, returns and exchanges, fulfillment, product and shipping protection, and fraud detection. It works with more than 1,000 merchant partners across multiple industries and is headquartered in downtown San Francisco. The team is remote-first.
Requirements
- At least 5 years of experience in product data science or consulting, with a strong emphasis on strategic thinking and a track record of driving business impact.
- Strong statistical foundations in experimentation, causal inference, forecasting, and modeling.
- Experience working with backend Product and Engineering teams to implement product roadmaps.
- Expert knowledge of SQL, Python, A/B testing, and GitHub.
- Hands-on experience with Snowflake and dbt, or close equivalents.
- Intellectual curiosity and willingness to think beyond the revenue organization and prioritize what is best for the business holistically.
- Empathetic, humble, collaborative, comfortable with ambiguity, and able to take high ownership in a remote-first team.
- Excited about AI tools such as Claude and Gemini and eager to use them to complement workflow.
- Advanced degree in data science, analytics, economics, statistics, or a similar quantitative field.
Responsibilities
- Own and identify innovative strategies across the revenue waterfall to grow and recover revenue in collaboration with client-facing teams.
- Build data-backed talk tracks and narratives for Revenue teams to optimize and grow existing partnerships, using insights from testing, Monte Carlo simulations, and/or machine-learning models.
- Test optimization ideas, validate them with data, and make the case to Product and Engineering teams to turn successful ideas into product features.
- Own, refine, and improve data pipelines; define data structures; and use advanced tracking methodologies to uncover revenue opportunities.
- Set a standard for analytical thinking and excellence on the team.
Benefits
- Full medical, dental, and vision benefits.
- Stock in an early-stage startup.
- Generous, flexible paid time off policy.
- 401(k) with financial guidance from Morgan Stanley.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
