Data Scientist, Enterprise Analytics

The job

LIVE Live feed (private-sector employer) Source: The Muse public API · Data: listed 2026-10-31

Job description

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.

*Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.

An Overview of this role

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. This is a strategic and hands-on role. You’ll apply statistical, experimentation, and machine learning methods to forecast outcomes, explain what drives activation, conversion, expansion, and retention, and size opportunities. You’ll also support the company-level reporting and GTM performance views that executives use to run the business, covering consumption, ARR, and first orders.

What you’ll do

• 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, and communicate their impact clearly to non-technical audiences.
• Build and productionize machine learning models - such as propensity, product-qualified lead (PQL) scoring, churn, and expansion models - including training, validation, testing, and feature engineering, using MLOps practices and tooling (CI/CD for ML pipelines, model registries, automated retraining, and monitoring) to move work reliably from notebook to production
• Design, run, and evaluate growth experiments (A/B tests and quasi-experiments) on onboarding, pricing and packaging, and upgrade flows, and measure their impact on activation, conversion, and retention
• Build and operationalize agentic workflows for analysis, modeling, and pipeline automation, with evaluation and monitoring that keep agent-generated insights accurate, traceable, and trustworthy.
• Contribute to GitLab’s Semantic Layer enabling stakeholders and agents to self-serve metrics using trusts and tested sources.
• Write production-grade Python and SQL that meets internal standards for style, maintainability, and performance in a high-scale database environment; maintain and advocate for these standards through code review

What you’ll bring

• 3-5 years of professional experience in GTM analytics, data science, or a similar technical role
• 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, clustering, and survival analysis
• Deep, hands-on understanding of SQL in cloud data warehouses (like Snowflake SQL), including working with product usage and event data, and in business intelligence tools (Looker, Tableau, Hex, or similar)
• Experience using Python for statistical modeling, machine learning, and production data science. With hands-on experience in pandas, NumPy, scikit-learn, Jupyter, and related libraries such as LightGBM and XGBoost
• Hands-on experience building agentic workflows with AI coding agents (e.g., Claude Code, OpenCode, or similar), including connecting agents to the right context, tools, and platforms such as MLflow, and evaluating their output for accuracy and reliability.
• Experience working in a B2C company working with motions and metrics, including Consumption, CRR, ARR, and Churn & Contraction
• Self-motivated and self-managing, with strong organizational skills
• Ability to use GitLab and to thrive in a fully remote organization

About the Team

The Enterprise Analytics team builds the trusted data products and insights behind GitLab’s Company wide sales, revenue, and finance reporting. We work across the business on metrics including First Orders, pipeline, CRR, ARR, and other key indicators, helping leaders make informed decisions and teams understand how their work contributes to GitLab’s growth.

The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through 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. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.

How GitLab Supports Full-Time Employees

• Benefits to support your health, finances, and 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 welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.

Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.  

Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us.

GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless 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 (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process.

Explore around this job

Field: Technology Sub-niche: Data, analytics and AI All jobs at GitLab Pay for this occupation (BLS) All 119 open jobs for this occupation

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About the role

This is a Senior Level role in the Technology field (Data, analytics and AI) at GitLab. Senior roles usually expect substantial experience, ownership of results and often the ability to guide others.

The closest occupation in the official wage statistics is Data scientists (a match by name, so treat it as an estimate). Nationally its median pay is $120,230 a year (BLS OEWS, May 2025), employment is projected to change by +34.6% between 2025 and 2035, and the typical entry route is: Bachelor's degree.

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Same sub-niche: Data, analytics and AI

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FAQ

What is the Data Scientist, Enterprise Analytics job at GitLab?

A senior level role in technology (data, analytics and ai) listed 8 days ago. The full description is on this page and on The Muse.

Where is this job?

Remote / flexible (United States). A remote or flexible location is listed; confirm with the employer which states are accepted.

How do I apply?

Use the "View this job and apply on The Muse" button. AtiveSite does not receive applications.

How much does it pay?

The listing does not publish pay. For the closest occupation (Data scientists) the national median is $120,230 a year (BLS OEWS, May 2025).

What is the cost of living there?

See the state or country guide for rent, income and taxes.

How old is this listing?

It was posted on 2026-10-31 (8 days ago). Jobs older than 90 days are not shown.

Are there similar jobs?

Yes: browse data, analytics and ai jobs in the United States.

Sources and terms

• Job data: The Muse public API (listing dated 2026-10-31). The job disappears from this site when it disappears from the source.
• Wages and projections: BLS OEWS (May 2025) and Employment Projections 2025–35.
• City and county figures: Census Bureau ACS 2020–2024, BEA, BLS QCEW and LAUS, NASA POWER climatology; distances from Census Gazetteer coordinates.

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Sources

• BLS OEWS (wages and employment by occupation, May 2025)
• BLS Employment Projections 2025–35
• BLS Local Area Unemployment Statistics
• BLS JOLTS
• BLS State and Metro Area Employment
• Census Bureau American Community Survey (via Census Reporter)
• BEA GDP by state and Regional Price Parities
• IRS 2026 tax adjustments
• U.S. Department of Labor, minimum wage by state
• Tax Foundation state income tax rates 2026
• USAJOBS
• USCIS
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• NASA POWER climatology
• GeoNames / Census Gazetteer (coordinates)