Data Scientist, Enterprise Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Integrate with business teams to establish yourself as a reliable partner in facilitating insight generation and strategic decision-making throughout GTM.

• Conduct exploratory data analysis to identify behavioral trends, long-term patterns, and the primary drivers and levers influencing business performance, effectively communicating these insights to non-technical audiences.

• Develop and implement machine learning models including propensity, product-qualified lead (PQL) scoring, churn, and expansion models, covering training, validation, testing, feature engineering, and MLOps practices.

• Design, execute, and assess growth experiments (A/B tests and quasi-experiments) related to onboarding, pricing, packaging, and upgrade flows, measuring the impact on activation, conversion, and retention rates.

• Create and operationalize agentic workflows for analysis, modeling, and pipeline automation, ensuring evaluation and monitoring for precise, traceable, and reliable insights.

• Contribute to GitLab’s Semantic Layer, allowing stakeholders and agents to independently access metrics from trusted and validated sources.

• Write production-quality Python and SQL code while upholding coding standards through code review processes.

• Assist in company-wide reporting and GTM performance insights focusing on consumption, ARR, and initial orders.

⛳️ Requirements

• 3-5 years of professional experience in GTM analytics, data science, or a comparable technical position.

• Proven ability to convert ambiguous business challenges into clear, measurable inquiries and effectively communicate technical concepts to non-technical stakeholders.

• Familiarity with experimentation and causal inference (A/B testing, power analysis, quasi-experimental methods) along with statistical and machine learning techniques such as regression, classification, clustering, and survival analysis.

• Extensive, hands-on experience with SQL in cloud data warehouses (like Snowflake SQL), including working with product usage and event data, as well as in business intelligence tools (Looker, Tableau, Hex, or similar).

• Proficiency in using Python for statistical modeling, machine learning, and production data science, with practical experience in libraries such as pandas, NumPy, scikit-learn, Jupyter, and others like LightGBM and XGBoost.

• Practical experience in creating agentic workflows utilizing AI coding agents (e.g., Claude Code, OpenCode, or similar), including linking agents to the appropriate context, tools, and platforms like MLflow, and assessing their outputs for accuracy and reliability.

• Background in a B2C company, working with metrics and motions including Consumption, CRR, ARR, and Churn & Contraction.

• Self-driven and self-managing, possessing strong organizational skills.

• Capable of utilizing GitLab and thriving in a fully remote work environment.

🏝️ Benefits

• Benefits designed to support your health, finances, and overall well-being.

• Flexible Paid Time Off.

• Team Member Resource Groups.

• Equity Compensation & Employee Stock Purchase Plan.

• Growth and Development Fund.

• Parental Leave.