Senior Manager, Data Science

GitLab

5d•Remote

About The Position

The Senior Manager, Data Science leads Product Data Science, a team of six Data Scientists within GitLab's data organization, and reports to the Director of Data Science. The role has two mandates: drive immediate product impact by setting the analytical agenda and ensuring the team's work informs decisions, and help build a unified Data Science function by defining excellence for Data Scientists who combine analytics and data science and developing the team to that standard. The manager leads primarily through others while contributing hands-on when needed, such as reviewing models, pressure-testing analyses, or writing queries. Product Data Science combines Data Science and Analytics. The team partners with Product and Engineering to guide what to build, measure outcomes, and understand how customers gain value from GitLab. The role will help the team focus on experimentation, causal inference, production models, and actionable recommendations as AI drives new opportunities in GitLab's consumption business.

Requirements

10+ years of experience 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 sense and a track record of being a trusted partner to Product and Engineering leaders.
Exceptional communication skills, including the ability to make complex problems and findings clear to audiences ranging from Product leaders to executives and to coach others to do the same.
Ability to thrive in ambiguity by structuring undefined problems, gathering relevant information, and making sound decisions on high-risk, cross-team issues.
Willingness to challenge, offer dissenting views, ask tough questions, and foster inclusive debate.
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 skills (Snowflake preferred) and strong Python skills, with experience taking machine learning models to production.
Fluency with AI tools and sound judgment about when AI output can be trusted.
Ability to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values.

Nice To Haves

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.
An advanced degree in a quantitative field.

Responsibilities

Set a long-range vision and roadmap for Product Data Science, connecting team goals to company strategy.
Own prioritization and trade-offs across product areas, adapting the team as priorities change.
Partner with Product and Engineering leaders on complex and urgent questions, selecting an appropriate approach such as a deep dive, experiment, or production model.
Raise risks and resource gaps early and present senior leaders with clear options to support timely decisions.
Hire, coach, and retain a high-performing team; build career paths, respond to team feedback, and make talent decisions as needed.
Build a high-trust culture of urgency and accountability, with open communication, predictable progress updates, and timely, high-quality delivery.
Set standards for experimentation, causal inference, metric definition, and production modeling.
Contribute hands-on when needed by reviewing models, pressure-testing analyses, or writing queries.