Staff Data Scientist, GTM
Join Cursor as a Staff Data Scientist to build data infrastructure and insights for the rapidly growing GTM Analytics team.
Skills & Technologies
AI in the day-to-day
Define how GTM interacts with data in an AI-first way.
Joblaze summary
In this role, the Staff Data Scientist will take charge of developing and maintaining the data models and pipelines that underpin the GTM analytics efforts at Cursor. Proficiency in SQL and experience with complex datasets are essential, along with a strong background in building forecasting and capacity models. This position is ideal for a senior-level candidate with a solid analytics foundation, particularly those familiar with GTM and revenue analytics, who thrive in a fast-paced, collaborative environment.
Joblaze insights
- Listed today on Joblaze — tracked directly from Cursor's career page.
- Cursor has 95 other open roles including Solutions Architect - APJ, Community Operations Manager , Solutions Architect.
- 1056 active SQL roles on Joblaze right now.
- 25 active Data Pipelines roles on Joblaze right now.
- 7 active GTM roles on Joblaze right now.
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: GTM, Data Pipelines, data models, forecasting, SQL, revenue analytics.
- What seniority level is this role?
- Cursor targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Staff Data Scientist, GTM role at Cursor.
From the original posting
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.