$234,000 – $316,500
Listed on Intuit’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Lead a team of senior data scientists building Intuit's governed data foundation and semantic layers that power Customer Success analytics and AI. This hands-on management role combines technical direction-setting with people leadership, requiring someone who can establish data standards, influence executives, and oversee multi-million-dollar impact initiatives while staying credible in deep technical discussions.
Our summary, not Intuit’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, Operations Research, Engineering, or related quantitative field
- 14+ years in data science, analytics, or data platform work
- 5+ years directly managing data scientists or analytics engineers
- Hands-on technical proficiency in SQL and Python sufficient to review architecture and code critically
- Experience leading teams that deliver governed data foundations, metric standardization, domain modeling, and data quality programs at enterprise scale
- Experience with modern cloud data platforms and pipeline orchestration
- Track record building AI/GenAI or agentic capabilities for data operations automation
- Demonstrated ability to define business-shaping metrics and influence Director and VP-level stakeholders without direct authority
- Experience owning a multi-million-dollar impact portfolio with financial case development and executive reporting
- Strong communication skills translating complex technical and governance concepts for executive audiences
Nice to have
- Experience with data governance and compliance regimes (IRS 7216, GDPR, CCPA)
- Fine-grained access control implementation at scale
- Semantic layers, knowledge graphs, or knowledge-layer design for AI and agent consumption
- Experimentation and causal inference depth (A/B testing at scale, difference-in-differences, propensity methods, synthetic control)
- Background in Customer Success, customer experience, contact center, or FinTech analytics
- Track record establishing cross-functional governance mechanisms like schema registries, data stewardship roles, or change-notification processes