Senior Manager, Data Science
New
G
GitLabDevSecOps software
Remote, United StatesFull-TimeManager
Salary152,800 - 259,200 USD per year
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Job Details
- Experience
- 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
- Required Skills
- PythonSQLMachine LearningSnowflakeProduct AnalyticsData scienceGitLab
Requirements
- Bring 10+ years of experience in data science, product analytics, or a related field.
- Have 3+ years managing data science or analytics teams in B2B SaaS or tech.
- Demonstrate strong product sense and a track record partnering with Product and Engineering leaders.
- Communicate complex problems and findings clearly to audiences ranging from product leaders to executives, and coach others to do the same.
- Structure ambiguous problems, gather relevant information, and make sound decisions on high-risk, cross-team issues.
- Bring expertise in statistics and experimentation, including hands-on use of difference-in-differences, synthetic control, and propensity score matching.
- Have expert SQL skills; Snowflake is preferred.
- Have strong Python skills and experience taking ML models to production.
- Use AI tools fluently and exercise sound judgment about when AI output can be trusted.
- Be able to use GitLab and work effectively in an all-remote, asynchronous company.
Responsibilities
- Set a long-range vision and roadmap for Product Data Science and connect team goals to company strategy.
- Prioritize work and trade-offs across product areas, adapting the team as priorities shift.
- Partner with Product and Engineering leaders on complex questions, selecting a deep dive, experiment, or production model as appropriate.
- Raise risks and resource gaps early and present senior leaders with clear options.
- Hire, coach, and retain the team, build career paths, act on feedback, and make talent decisions.
- Build a high-trust culture of urgency and accountability, with open communication and predictable progress updates.
- Set standards for experimentation, causal inference, metric definition, and production modeling.
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