Data Scientist, GTM

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code. Cursor is expanding rapidly into the Enterprise AI coding market, and our GTM organization is scaling just as fast. As one of the first hires on our GTM Analytics team, you'll be the most senior IC on the team — both building the data infrastructure GTM runs on and turning it into the metrics, models, and insights leadership uses to make decisions. About the role This is a hands-on, high-leverage role. You'll set the technical and analytical bar for the team. You'll own the GTM data models and pipelines that matter, build a trustworthy semantic layer reps and leadership can build from, and use that foundation to answer the hard questions about what's driving pipeline, conversion, and retention. You'll define how GTM interacts with data in an AI-first way, work with the GTM Apps team and RevOps to keep tooling consistent, and partner with the product Data and Enterprise Engineering teams to get the data you need. What you’ll do - Own the GTM data models and pipelines that power analysis - building and maintaining them, setting high quality standards, and creating a safe and consistent semantic layer GTM can build on. - Run deep-dive analyses on what's driving (and blocking) revenue: funnel conversion, segment performance, customer success, and rep productivity. - Optimize the forecasting, quota, and capacity models leadership plans against, and pressure-test the assumptions behind them. - Define how GTM interacts with data in an AI-first way—what's self-serve via Cursor and what's prebuilt into governed dashboards and applications. - Partner with the product Data and Enterprise Engineering teams to ensure GTM has the data it needs and uses consistent pipelines, definitions, and models wherever possible. You may be a fit if - Your SQL is exceptional (non-negotiable), and you're fluent working across large, complex datasets. - You've built and maintained production data pipelines and models, and you pick up unfamiliar data structures quickly—CRM and GTM systems included. - You've built forecasting, quota, or capacity models, and you're a strong modeler in both code and spreadsheets. - You're comfortable with experimentation and causal inference, and you know when a quick read beats a rigorous one—and when it doesn't. - You can operationalize metrics and tooling for non-technical stakeholders so they can self-serve. - You have strong analytical judgment and can move between the big picture and the details—from "how should we measure GTM health?" to "why is this one segment's conversion off?" - Direct experience with GTM, revenue, or sales analytics is preferred, but a strong analytics or data-science background and the drive to go deep on the GTM domain matter more. - You operate with high ownership, are comfortable pushing back on senior leaders, and bias toward durable systems over one-off decks.

You may be a fit if: - Your SQL is exceptional (non-negotiable), and you're fluent working across large, complex datasets. - You've built and maintained production data pipelines and models, and you pick up unfamiliar data structures quickly—CRM and GTM systems included. - You've built forecasting, quota, or capacity models, and you're a strong modeler in both code and spreadsheets. - You're comfortable with experimentation and causal inference, and you know when a quick read beats a rigorous one—and when it doesn't. - You can operationalize metrics and tooling for non-technical stakeholders so they can self-serve. - You have strong analytical judgment and can move between the big picture and the details—from "how should we measure GTM health?" to "why is this one segment's conversion off?" - Direct experience with GTM, revenue, or sales analytics is preferred, but a strong analytics or data-science background and the drive to go deep on the GTM domain matter more. - You operate with high ownership, are comfortable pushing back on senior leaders, and bias toward durable systems over one-off decks.