Cursor is looking to establish growth as a company priority and drive product strategy to help users see value and increase usage.
Requirements
- You’re fluent in SQL and Python, and can write pipelines to unblock yourself.
- You have strong opinions about AB testing, conversion funnels, and growth accounting.
- Hands-on experience with dbt and analytics engineering.
- Machine learning applied to growth problems: LTV prediction, churn modeling, attribution.
Responsibilities
- Designing and analyzing experiments to help users activate earlier and land on the right subscription tier.
- Building foundational datasets and models to segment users and customers.
- Evaluating the health of each tier and identifying opportunities for tier differentiation.
- Understanding user–AI interactions in Cursor and how they drive growth and financial metrics.
- Define, track, and own metrics like conversion and self-serve revenue that multiple teams and leadership depend on.
- Run experiments end-to-end: design, analyze, and translate into clear product recommendations.
- Build pipelines, dashboards, and analyses that make self-serve insights accessible and trustworthy.
Other
- As an early member of Cursor’s data team, this will be a hands-on role: partner with leadership to establish growth as a company priority, work hands-on with the entire data stack, and drive product strategy that helps our users quickly see Cursor's value and grow their usage.
- You're scrappy, pragmatic, and thrive in environments where you can work across multiple product areas at once.
- You’ve worked directly on Growth, especially product-led or pricing initiatives, and you know how to turn data into decisions that move metrics.
- Partner with area leads in Growth, Enterprise, Finance, and Product to shape data-informed decisions across the business.
- Establish data culture and foundations as an early member of the data team.
