153K–259K USD / year
Senior Manager, Data Science
DataRemote — United States
Published on 2026-10-30
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About this role
Lead GitLab’s Product Data Science team, setting its roadmap and ensuring its analyses and models influence product decisions. Help combine analytics and data science into a unified function, while remaining hands-on for high-impact work.
About the company
GitLab is a DevSecOps platform that brings source control, CI/CD, security, and project management into a single application. It helps engineering teams plan, build, secure, and ship software faster.
The team
Product Data Science: a team of six Data Scientists within GitLab’s data organization, reporting to the Director of Data Science.
Stack
SQLSnowflakePython
What you'll do
- Set the team’s long-range vision, roadmap, priorities, and resource trade-offs.
- Partner with Product and Engineering leaders to address complex questions through analysis, experiments, or production models.
- Raise risks and resource gaps early and present decision options to senior leaders.
- Hire, coach, and retain a high-performing team; build career paths and make talent decisions.
- Establish standards for experimentation, causal inference, metric definition, and production modeling.
- Build a culture of accountability, open communication, and reliable delivery.
What we're looking for
- 10+ years in data science, product analytics, or a related field, including 3+ years managing data science or analytics teams in B2B SaaS or technology.
- Strong product judgment and a record of partnering with Product and Engineering leaders.
- Exceptional communication skills and ability to explain complex findings to varied audiences.
- Able to structure ambiguous problems and make sound decisions on high-risk, cross-team issues.
- Deep expertise in statistics and experimentation, including hands-on use of quasi-experimental methods such as difference-in-differences, synthetic control, and propensity score matching.
- Expert SQL and strong Python skills; experience taking ML models to production.
- Fluent with AI tools and able to judge when their output is trustworthy.
- Able to work effectively in an all-remote, asynchronous environment and use GitLab.
Nice to have
- Experience with developer tools, DevSecOps, or product-led growth products.
- Experience measuring adoption and quality of AI-powered product features.
- Internal or external thought leadership in data science or analytics.
- Advanced degree in a quantitative field.
Benefits
- Flexible paid time off
- Equity compensation and employee stock purchase plan
- Parental leave
- Growth and development fund
- Benefits supporting health, finances, and well-being
- Team member resource groups