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 expertise in leading Data Science teams, driving product impact through analytical strategies, and fostering a high-trust culture. Proficient in statistics, experimentation, and production modeling, with strong communication skills to engage with Product and Engineering leaders.
Highest-signal resume keywords
Data Science LeadershipStatistical ExpertiseSQL ProficiencyPython ProgrammingProduct Analytics
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ScienceProduct AnalyticsStatisticsExperimentationMachine LearningSQLPythonCausal InferenceQuasi-Experimental MethodsMetric Definition
Soft Skills
Exceptional CommunicationProblem StructuringInclusive DebateTeam BuildingDecision Making
Tools & Technologies
SnowflakeAI ToolsGitLabDevSecOpsDeveloper Tools
Certifications & Qualifications
Advanced Degree in Quantitative Field
Industry Keywords
B2B SaaSProduct-Led GrowthThought LeadershipAnalyticsRemote Working Competencies
Tech Stack
Tools & technologiesPythonSnowflakeSQL
About the role
Key responsibilities & impact- Lead Product Data Science, a team of 6 Data Scientists within GitLab's data organization, reporting to the Director of Data Science
- Drive product impact by setting the analytical agenda for product areas and ensuring the team's work changes decisions
- Build the merged Data Science function by defining excellence for Data Scientists and growing the team to that standard
- Set a long-range vision and roadmap for Product Data Science and connect team goals to company strategy
- Own prioritization and trade-offs across product areas and adapt the team as priorities shift
- Partner with Product and Engineering leaders on complex and urgent questions, selecting deep dives, experiments, or production models as appropriate
- Raise risks and resource gaps early and present senior leaders with clear options for timely decisions
- Hire, coach, and retain a high-performing team; build career paths, act on feedback, and make talent decisions
- Build a high-trust culture of urgency and accountability with open communication, predictable progress sharing, and timely quality delivery
- Set standards for experimentation, causal inference, metric definition, and production modeling
- Review models, pressure-test analyses, and write queries hands-on when needed
Requirements
What you’ll need- 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 communication skills, including explaining complex problems and findings to audiences from Product leaders to executives
- Ability to structure undefined problems, gather relevant information, and make sound decisions on high-risk, cross-team issues
- Ability to offer dissenting views, ask tough questions, and foster inclusive debate
- Deep expertise in statistics and experimentation, including hands-on use of quasi-experimental methods: difference-in-differences, synthetic control, and propensity score matching
- Expert SQL, with Snowflake preferred
- Strong Python skills
- Experience taking ML models to production
- Fluency with AI tools and sound judgment on 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
- Experience with developer tools, DevSecOps, or product-led growth products is nice to have
- Experience measuring adoption and quality of AI-powered product features is nice to have
- Thought leadership in data science or analytics, internally and externally is nice to have
- Advanced degree in a quantitative field is nice to have
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
- All-remote work arrangement