Data Scientist, Enterprise Analytics
Gitlab
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.
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...Mercor is working with a leading AI research lab on a project to improve how AI systems do real-world data science and data engineering work. We’re looking for senior data scientists and data engineers who have deep experience at top technology, quantitative or financial firms....Hourly payContract work- ...passionate, loyal, and growing community, and we’re looking for people who want to help us build something truly special. Senior Data Scientist, Growth We’re looking for an experienced Data Scientist to join one of our cross-functional squads at Shakepay. You’ll work closely...Long term contractFull time
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...weeks ~60% Within 3 months ~80% Why this role This Data Scientist - AI Reviewer Expert role pays $150/hr for your STEM judgment... ...after a project closes. That net-30 schedule is standard for enterprise expert networks, but it's slower than the weekly payouts some...Hourly payRemote work- ...Build and validate data pipelines for AI performance evaluation projects. About Turing... ...AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing... ...overall experience as a Data Engineer, Data Scientist, or Software Engineer (data-focused) ....Contract workPart timeFor contractorsFreelanceManual laborRemote work
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$45 - $90 per hour
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