Senior Manager, Data Science

As Senior Manager, Data Science, you'll lead Product Data Science: a team of 6 Data Scientists within GitLab's data organization, reporting to the Director of Data Science. You have two mandates:

1. Drive product impact now. Set the analytical agenda for your product areas and make sure the team's work changes decisions.
2. Build the merged Data Science function. Define excellence for a Data Scientist who blends analytics and data science, and grow the team to that bar.

You lead mainly through others, and step in hands-on when it matters: reviewing a model, pressure-testing an analysis, or writing the query yourself.

• Set a long-range vision and roadmap for Product Data Science, and show the team how its goals connect to company strategy
• Own prioritization and trade-offs across product areas, and adapt the team as priorities shift
• Be the go-to partner for Product and Engineering leaders on complex and urgent questions, choosing the right approach: a deep dive, an experiment, or a production model
• Raise risks and resource gaps early, and bring senior leaders clear options to drive timely decisions
• Hire, coach, and retain a high-performing team: build career paths, act on team feedback, and make tough talent decisions when needed
• Build a high-trust culture of urgency and accountability, where the team communicates openly, shares progress on a predictable cadence, and delivers quality results on time
• Set standards for experimentation, causal inference, metric definition, and production modeling

• 10+ years in data science, product analytics, or a related field, including 3+ years managing data science or analytics teams in B2B SaaS or tech
• Strong product sense and a track record as a trusted partner to Product and Engineering leaders
• Exceptional communicator who makes complex problems and findings clear to any audience, from Product leaders to executives, and coaches others to do the same
• Thrives in ambiguity: structures undefined problems, gathers the right information, and makes sound decisions on high-risk, cross-team issues
• Courage to challenge: offers dissenting views, asks tough questions, and fosters inclusive debate
• Deep expertise in statistics and experimentation, including hands-on use of quasi-experimental methods (difference-in-differences, synthetic control, propensity score matching)
• Expert SQL (Snowflake preferred) and strong Python, with experience taking ML models to production
• Fluent with AI tools, with sound judgment on when AI output can be trusted
• Able to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values

• Experience with developer tools, DevSecOps, or product-led growth products
• Experience measuring adoption and quality of AI-powered product features
• Thought leadership in data science or analytics, internally and externally
• Advanced degree in a quantitative field

Product Data Science brings Data Science and Analytics together into one function. Our Data Scientists are business partners first, pairing strong product judgment with deep skill in SQL, Python, statistics, and machine learning. We help Product and Engineering decide what to build, measure what worked, and understand how customers get value from GitLab.

The opportunity is growing fast. AI is driving growth in GitLab's consumption business, creating new ways for data to drive growth. As AI takes over routine reporting, the team focuses on the hard problems: experimentation, causal inference, production models, and recommendations leaders act on.