As a Data Scientist at GitLab on the Enterprise Analytics team, you’ll be a trusted analytical partner to Sales, Revenue Operations, and Finance, helping define how we measure go-to-market performance and where we invest to grow.
Embed yourself with business teams to become a trusted partner supporting insight generation and strategic decision making across GTM.
Perform exploratory data analysis to uncover behavioral trends, long-term patterns, and the key drivers and levers behind business performance…
Design, run, and evaluate growth experiments (A/B tests and quasi-experiments) on onboarding, pricing and packaging, and upgrade flows…
Build and operationalize agentic workflows for analysis, modeling, and pipeline automation, with evaluation and monitoring that keep agent-generated insights accurate, traceable, and trustworthy.
Demonstrated ability to translate ambiguous business problems into clear, measurable questions and communicate technical concepts effectively to non-technical stakeholders.
Experience with experimentation and causal inference (A/B testing, power analysis, quasi-experimental methods) and with statistical and machine learning methods such as regression, classification…
Deep, hands-on understanding of SQL in cloud data warehouses (like Snowflake SQL), including working with product usage and event data…
Experience using Python for statistical modeling, machine learning, and production data science. With hands-on experience in pandas, NumPy, scikit-learn, Jupyter…
Experience: Mid-level · 3–5 years
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