Cursor
Technology
StaffDataScientist,GTM
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Data Scientist, GTM at Cursor. Skills: Data modeling, Data pipelines, Forecasting, Causal inference. Own GTM data models. Own GTM data pipelines”
Industry & Context.
Analytical judgment
What You'll Do.
Own GTM data pipelines
Set quality standards
Create semantic layer
Run deep-dive analyses
Optimize forecasting models
Optimize quota models
Optimize capacity models
Pressure-test model assumptions
Define GTM data interaction
Partner with Data teams
Partner with Engineering teams
How You'll Work.
Team & Collaboration
GTM Apps team; RevOps; Product Data teams; Enterprise Engineering teams
Full Job Description
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 E
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