Data Scientist, Enterprise Analytics

Royper Royco LLC; United States; Remote; USD 86,000 - 176,000; Full time

Benefits offered by this job

Equity Compensation & Employee Stock-P

Growth and Development Fund

Parental Leave

Flexible Paid Time Off

Job summary

GitLab is seeking a Data Scientist for the Enterprise Analytics team to forecast go-to-market performance and size opportunities. You will apply statistics, experimentation, and machine learning to drive activation, conversion, expansion, and retention across GTM metrics.

You’ll embed with Sales, Revenue Operations, and Finance, build production-grade code in Python/SQL, and contribute to semantic data layers enabling self-serve metrics for executives and teams.

Qualifications

• Translate ambiguous business problems into measurable questions.
• Explain technical concepts to non-technical stakeholders.
• Design and evaluate growth experiments (A/B tests).
• Write production-grade Python and SQL for large-scale data environments.
• Work with GTM metrics such as ARR, CRR, and churn.

Responsibilities

• Embed with business teams to become a trusted analytics partner.
• Perform exploratory data analysis to uncover trends and drivers.
• Build and productionize ML models (propensity, PQL, churn, expansion).
• Design, run, and evaluate growth experiments (A/B tests).
• Develop agentic workflows and automate analysis pipelines.
• Contribute to GitLab’s Semantic Layer for self-serve metrics.
• Write clean, scalable Python/SQL in a high-scale environment.

Skills

GTM analytics

SQL (Snowflake)

Python for ML

A/B testing

Communication to non-technical

Tools

Looker

Tableau

Hex

MLflow

Jupyter

LightGBM

XGBoost

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