From the listing
About the role
GitLab is the intelligent orchestration platform for DevSecOps, enabling organizations to increase developer productivity, improve operational efficiency, and accelerate digital transformation. More than 50 million registered users and over 50% of the Fortune 100 trust GitLab to ship secure software faster.
As a Data Scientist on the Enterprise Analytics team, you will be a strategic and hands-on partner to Sales, Revenue Operations, and Finance. You will apply statistical, experimentation, and machine learning methods to forecast outcomes and explain business drivers like activation, conversion, and retention.
The Enterprise Analytics team builds the trusted data products and insights behind GitLab’s company-wide sales, revenue, and finance reporting. The team helps leaders make informed decisions by analyzing key indicators such as First Orders, pipeline, CRR, and ARR.
What you'll do
- Embed with business teams to support insight generation and strategic decision making across GTM.
- Perform exploratory data analysis to uncover behavioral trends and key drivers behind business performance.
- Build and productionize machine learning models including propensity, PQL scoring, churn, and expansion models using MLOps practices.
- Design, run, and evaluate growth experiments and A/B tests on onboarding, pricing, and upgrade flows.
- Build and operationalize agentic workflows for analysis, modeling, and pipeline automation.
- Contribute to GitLab’s Semantic Layer to enable stakeholder self-service for metrics.
- Write production-grade Python and SQL that meets internal standards for style and performance.
What they're looking for
- 3-5 years of professional experience in GTM analytics, data science, or a similar technical role.
- Demonstrated ability to translate ambiguous business problems into measurable questions.
- Experience with experimentation, causal inference, and statistical methods like regression and survival analysis.
- Deep, hands-on understanding of SQL in cloud data warehouses like Snowflake.
- Experience using Python for statistical modeling and machine learning (pandas, NumPy, scikit-learn, XGBoost).
- Hands-on experience building agentic workflows with AI coding agents.
- Experience working in a B2C company with metrics like Consumption, CRR, ARR, and Churn.
- Ability to thrive in a fully remote organization.
From the company page
Gitlab benefits
◉ Remote policy · in their words
“We've scaled as an asynchronous, no-office company that's consistently recognized as a great place to work.”
Pulled from their careers page · verified by Atlas
The hot takeJeff's read on Gitlab
GitLab has put more effort into their employee marketing and policies than 99.99% of the companies we've researched over the years. Seriously, their handbook is absolutely massive.
The ONLY thing that throws me off about them is an unclear statement about their stance on what "work from anywhere" actually means. They say:
"All-remote means that each individual in an organization is empowered to work and live where they are most fulfilled."
But they also say that hey need to have an entity in your home country in order to be hired, so I'd love to know if they have a list of the countries they will hire from.