Director, Data Science

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 valuesand 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 RoleAs Director, Data Science, you'll lead GitLab's Product, Sales, and Finance Data Science teams and report to the VP of Data & Insights. You have two mandates:
Make Data Science a driver of growth.
Connect the team's work to GitLab's biggest priorities: supporting product innovation, making sure what we launch is improved and scaled with data, improving product adoption through our GTM motions, and growing the consumption business. Make sure the work changes decisions at the executive level.
Set the bar for great data science.
Define what makes a great Data Scientist at GitLab, from business partnership to technical rigor, and develop managers who build teams where everyone shows up to that standard.
You lead through your managers with an overall team size of 12 including data scientists and analysts, ensuring direction with the team across the data organization, and staying close enough to the work to pressure-test the analyses and models that matter most.
What you’ll do
Build trusted relationships with executives across Product, Finance, and GTM, and act as their thought partner, shaping the questions the business should be asking, not just answering them
Own investment and prioritization across teams: decide where Data Science spends its time, and make trade-offs visible to senior leaders
Lead high-impact, cross-functional programs, such as driving new product adoption and growing our consumption business, from strategy through measurable business impact
Coach and mentor managers and senior ICs to grow as leaders, building succession and a bench of future leaders
Hold a high talent bar, and make sure every teammate grows into a trusted thought partner in their area
Set org-wide standards for metric definition, causal inference, and predictive modeling, and the role of AI in each
Build a high-trust culture of urgency, accountability, and open communication, and act on engagement and feedback across teams
Partner with Analytics Engineering, Data Engineering, and other data teams across the company to solve data opportunities together, aligned on a shared data and AI roadmap
What you’ll bring
12+ years in data science, product analytics, or a related field, including 6+ years leading teams and 3+ years managing managers in B2B SaaS or tech
Track record of building and scaling a data science or analytics organization that executives treat as a strategic partner
Strong business acumen across product and go-to-market, with experience connecting data work to revenue and growth outcomes
Executive presence: communicates complex findings and trade-offs clearly to the C-suite, and coaches managers to do the same
Deep expertise in statistics, experimentation, and causal inference, with enough technical depth in SQL, Python, and ML to guide and pressure-test the team's work
Clear point of view on how AI is reshaping data science and analytics, and experience leading teams through that shift
Able to use GitLab, thrive in an all-remote, asynchronous company, model and coach 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 with usage-based or consumption pricing models
Experience merging or restructuring data science and analytics teams
Thought leadership in data science or analytics, internally and externally
About the TeamData Science at GitLab brings Data Science and Analytics together into one function. Our Data Scientists are business partners first, pairing strong business judgment with analytical rigor and statistical expertise. We help leaders decide where to invest, 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 routine reporting becomes self-serve, the team focuses on the hard problems: experimentation, causal inference, production models, and recommendations leaders act on.
The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data,and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity. 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.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process .
As set forth in GitLab’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.
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