FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive leadership in data science and analytics, with a strong focus on connecting data initiatives to business growth and product innovation. Possesses deep expertise in statistics, causal inference, and AI, while fostering a high-trust culture and effective communication with executives.
Highest-signal resume keywords
Data Science LeadershipBusiness AcumenCausal Inference ExpertiseExecutive CommunicationAI Integration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
StatisticsCausal InferencePredictive ModelingSQLPythonMachine LearningData AnalyticsExperimentationData Science StrategyMetric Definition
Soft Skills
CoachingMentoringBuilding RelationshipsOpen CommunicationAccountability
Tools & Technologies
GitLabAnalytics EngineeringData EngineeringDevSecOpsDeveloper Tools
Industry Keywords
B2B SaaSProduct AnalyticsGo-To-Market StrategyConsumption Pricing ModelsData Science Organization
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Lead GitLab's Product, Sales, and Finance Data Science teams and report to the VP of Data & Insights
- Connect Data Science work to product innovation, product adoption, go-to-market motions, and consumption-business growth
- Ensure Data Science work changes decisions at the executive level
- Lead a team of 12 data scientists and analysts through managers
- Build trusted relationships with executives across Product, Finance, and GTM
- Own investment and prioritization across teams and make trade-offs visible to senior leaders
- Lead high-impact, cross-functional programs from strategy through measurable business impact
- Coach and mentor managers and senior ICs, building succession and future leadership capacity
- Set organization-wide standards for metric definition, causal inference, predictive modeling, and AI
- Build a high-trust culture of urgency, accountability, and open communication
- Partner with Analytics Engineering, Data Engineering, and other data teams on a shared data and AI roadmap
Requirements
What you’ll need- 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
- 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
Benefits
Comp & perks- Benefits to support your health, finances, and well-being
- Flexible Paid Time Off
- Team Member Resource Groups
- Equity Compensation & Employee Stock Purchase Plan
- Growth and Development Fund
- Parental Leave