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1 month ago

Data Scientist, GTM

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Staff Data Scientist for GTM analytics who will own the data models and pipelines powering revenue analysis, build a trustworthy semantic layer for GTM, run deep-dive analyses into funnel conversion and rep productivity, optimize forecasting and quota models, and define AI-first data interactions while partnering with Product Data and Enterprise Engineering to ensure consistent data definitions and pipelines.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•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.

Key Requirements

•Exceptional SQL skills and fluency with large, complex datasets
•Experience building production data pipelines and models, including CRM/GTM systems
•Experience building forecasting, quota, or capacity models and strong modeling abilities in code and spreadsheets
•Comfort with experimentation, causal inference, and knowing when quick reads vs rigorous analysis are appropriate
•Ability to operationalize metrics and tooling for non-technical stakeholders so they can self-serve

Experience:GTMSales analyticsRevenue analytics

Skills:SQLData modelingPipelinesData analysisDashboarding

Languages:English

Tech Stack:SQLCRMPipelinesBI tools

Company Brief

Cursor

Builds Cursor, an AI-powered development platform and code editor that helps developers write, review, and maintain code using large language models and developer-focused automation tools for enterprise engineering teams.

Industry: Developer Tools

Company Size: Large (251 to 1,000 employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: San Francisco, United States

Founded: 2022

Glassdoor: 3.0

Website LinkedIn Glassdoor

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Cursor

1 month ago

Data Scientist, GTM

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•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.

Key Requirements

•Exceptional SQL skills and fluency with large, complex datasets
•Experience building production data pipelines and models, including CRM/GTM systems
•Experience building forecasting, quota, or capacity models and strong modeling abilities in code and spreadsheets
•Comfort with experimentation, causal inference, and knowing when quick reads vs rigorous analysis are appropriate
•Ability to operationalize metrics and tooling for non-technical stakeholders so they can self-serve

Experience:GTMSales analyticsRevenue analytics

Skills:SQLData modelingPipelinesData analysisDashboarding

Languages:English

Tech Stack:SQLCRMPipelinesBI tools

Company Brief

Cursor

Industry: Developer Tools

Company Size: Large (251 to 1,000 employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: San Francisco, United States

Founded: 2022

Glassdoor: 3.0

Website LinkedIn Glassdoor