Data Scientist, Enterprise Analytics Remote, United States at GitLab

Data Scientist at GitLab - Enterprise Analytics

As a Data Scientist on the Enterprise Analytics team at GitLab, you will serve as a vital analytical partner to our Sales, Revenue Operations, and Finance departments. Your role is pivotal in defining how we measure go to market performance and strategically allocating investments for business growth.

This position is both strategic and hands on. You will apply advanced statistical, experimentation, and machine learning methods to accurately forecast outcomes, explain the drivers behind key business metrics such as activation, conversion, expansion, and retention, and appropriately size business opportunities.

Furthermore, you will support the creation of company-level reporting and Go to Market performance views that are essential for executives running the business, covering critical areas like consumption, ARR, and first orders.

What You Will Do

• Embed within business teams to function as a trusted partner, facilitating insight generation and strategic decision making across Go to Market functions.
• Conduct exploratory data analysis to uncover behavioral trends, long term patterns, and the primary drivers and levers impacting business performance, ensuring you communicate their impact clearly to non-technical audiences.
• Build and productionize machine learning models, including propensity scoring, product qualified lead (PQL) scoring, churn, and expansion models. This requires end to end management: training, validation, testing, and feature engineering, utilizing MLOps practices and tooling such as CI/CD for ML pipelines, model registries, automated retraining, and monitoring to reliably move work from notebook to production.
• Design, execute, and rigorously evaluate growth experiments, such as A/B tests and quasi experiments, focused on onboarding, pricing, and packaging, and accurately measure their effect on activation, conversion, and retention.
• Build and operationalize agentic workflows for complex analysis, modeling, and pipeline automation, complete with evaluation and monitoring to guarantee agent generated insights are accurate, traceable, and trustworthy.
• Contribute to GitLab’s Semantic Layer, empowering stakeholders and agents to self service metrics using vetted and tested data sources.
• Write production grade Python and SQL code that adheres to internal standards for style, maintainability, and performance within a high scale database environment, while maintaining and championing these standards through code reviews.

What You Will Bring

• 3 to 5 years of professional experience in GTM analytics, data science, or a closely related technical capacity.
• A proven capacity to translate ambiguous business problems into clear, measurable questions and effectively communicate complex technical concepts to non technical stakeholders.
• Experience with experimentation and causal inference methods, including A/B testing, power analysis, and quasi experimental designs, alongside statistical and machine learning techniques such as regression, classification, clustering, and survival analysis.
• A deep, practical understanding of SQL within cloud data warehouses like Snowflake SQL, particularly when working with product usage and event data, as well as experience using business intelligence tools such as Looker, Tableau, Hex, or similar platforms.
• Hands on experience utilizing Python for statistical modeling, machine learning, and production data science, including proficiency in pandas, NumPy, scikit learn, Jupyter, and related libraries like LightGBM and XGBoost.
• Hands on experience building agentic workflows leveraging AI coding agents, such as Claude Code or OpenCode, including connecting agents to the appropriate context, tools, and platforms like MLflow, and critically evaluating their output for precision and reliability.
• Experience operating within a B2C company, understanding motions and metrics like Consumption, Customer Recurring Revenue, Annual Recurring Revenue, and Churn and Contraction.
• Must be self motivated and self managing, possessing strong organizational skills.
• Ability to effectively use GitLab and excel within a fully remote organizational structure.

About the Team

The Enterprise Analytics team is responsible for building the reliable data products and insights that power GitLab’s company wide sales, revenue, and finance reporting. We collaborate across the business on key metrics including First Orders, pipeline, CRR, and ARR, enabling leaders to make well informed decisions and ensuring teams understand how their efforts contribute to GitLab’s overall growth.

The base salary range for this role, at its current level, is specified for residents of the United States only. This range is intended to reflect the base salary rate across locations throughout the US. Grade level and salary ranges are determined following interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. Please note that sales roles are also eligible for incentive pay targeted up to 100% of the offered base salary.

United States Salary Range: $86,400 - $176,400 USD

How GitLab Supports Full Time Employees

• 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.

Please note that we value interest from candidates at varying levels of experience; many successful candidates may not meet every single requirement. Furthermore, studies indicate that individuals from underrepresented groups are less likely to apply unless they meet every single qualification. If you are excited about this role, please apply and allow our recruiters to evaluate your application.

Regarding location, GitLab hires team members globally. While all of our roles are remote, some specific roles may have location based eligibility requirements. Our Talent Acquisition team is available to answer any location related questions after the recruiting process has begun. For details on our policies, please review our Recruitment Privacy Policy. GitLab is proud to be an equal opportunity workplace and an affirmative action employer. GitLab’s recruitment, employment, career development, advancement, promotion, and retirement policies are based solely on merit, irrespective of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status, or any other basis protected by law. GitLab strictly prohibits discrimination or harassment based on these characteristics. See GitLab’s EEO Policy. If you have a disability or special need that requires accommodation, please inform us during the recruiting process.

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