Senior Manager, Data Science

GitLab Inc.; Oregon; Hybrid; USD 153,000 - 259,000; Full time

Benefits offered by this job

Flexible Paid Time Off

Team Member Resource Groups

Equity Compensation & Employee Stock购买

Growth and Development Fund

Parental Leave

Job summary

GitLab is seeking a senior data science leader to drive product analytics and experimentation across our DevSecOps platform. You will define the analytical roadmap, build a cohesive Data Science function, and partner with Product and Engineering to influence decisions with rigorous analysis.

You will mentor a high-performing team, champion experimentation, and scale analytics to support growth and AI-enabled features. This is a remote role with global impact.

Qualifications

• 10+ years in data science, product analytics, or related field.
• 3+ years leading data science or analytics teams in B2B SaaS or tech.
• Strong partner to Product and Engineering leaders.
• Exceptional communicator to diverse audiences.
• thrives in ambiguity and makes high-risk decisions.
• Courage to challenge and foster inclusive debate.
• Deep expertise in statistics and experimentation.
• Hands-on ML with production experience.

Responsibilities

• Own and drive product data science impact across roadmaps.
• Set analytical agenda and ensure work informs decisions.
• Build and scale the merged Data Science function.
• Define excellence for data scientists and grow the team.
• Lead through others, with hands-on review and testing when needed.
• Align long-range vision with company strategy and priorities.
• Prioritize across product areas and adapt as needed.
• Partner with Product and Engineering on complex questions.
• Raise risks early and present clear options to leadership.
• Hire, coach, and retain high-performing team.

Skills

Data science leadership

Statistics & experimentation

SQL (Snowflake)

Python

ML in production

AI literacy

Communication

Product analytics

Ambiguity handling

Cross-functional collaboration

Education

Advanced degree in quantitative field

Tools

SQL (Snowflake)

Python

Job description

An Overview of this Role

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.

What you’ll do

• You have two mandates: Drive product impact now.
• Set the analytical agenda for your product areas and make sure the team's work changes decisions.
• 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

What you’ll bring

• 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

Nice to Have

• 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

About the Team

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.

United States Salary Range

United States Salary Range$152,800-$259,200 USD

How GitLab Supports Full-Time Employees

• Flexible Paid Time Off
• Team Member Resource Groups
• Equity Compensation & Employee Stock Purchase Plan
• Growth and Development Fund
• Parental Leave

Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.

Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification.

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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