Staff Data Scientist, GTM
Senior individual contributor on the GTM Analytics team building and owning data models, pipelines, semantic layers, deep-dive revenue analyses, forecasting models, and AI-first self-serve tooling for sales, pipeline, and retention insights. Requires exceptional SQL, production data pipeline experience, and strong modeling skills.
About the job
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 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.
Skills
SQL, Data Pipelines, Data Modeling, Forecasting Models, Quota Models, Capacity Models, Crm Systems, Gtm Systems, Analytics, Data Science
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