Data Scientist, GTM

Stack

Responsibilities

• ▹Own the GTM data models and pipelines: build, maintain, set quality standards, create a trustworthy semantic layer
• ▹Run deep-dive analyses on what drives and blocks revenue: funnel conversion, segment performance, customer success, rep productivity
• ▹Optimize forecasting, quota, and capacity models and pressure-test their assumptions
• ▹Define how GTM interacts with data in an AI-first way — self-serve via Cursor vs. governed dashboards and applications
• ▹Partner with product Data and Enterprise Engineering teams for consistent pipelines, definitions, and models

Requirements

• ▹Exceptional SQL skills (non-negotiable), fluent across large, complex datasets
• ▹Track record building and maintaining production data pipelines and models, picking up unfamiliar data structures quickly (including CRM and GTM systems)
• ▹Experience building forecasting, quota, or capacity models, strong modeling skills in both code and spreadsheets
• ▹Comfort with experimentation and causal inference, knowing when a quick read beats a rigorous one
• ▹Ability to operationalize metrics and tooling for non-technical stakeholders
• ▹Strong analytical judgment, moving between the big picture and the details

Nice to have

• ▹Direct experience with GTM, revenue, or sales analytics

Soft skills

About the company

Cursor's mission is to automate coding, and it is expanding rapidly into the enterprise AI coding market, with its GTM organization scaling just as fast.