Manager 3, Data Science - Data Foundations
- Compensation
- Not disclosed
- Location
- Mountain View, California, United States
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- BS or MS in Statistics, Mathematics, Computer Science, Economics/Econometrics, Operations Research, Engineering, or a related quantitative field
- 14+ years of experience in data science, analytics, or data platform work, including 5+ years directly managing data scientists or analytics engineers.
- Demonstrated success leading teams that deliver governed data foundations at enterprise scale metric standardization, domain/entity modeling, data quality programs, or data product ownership.
- Strong hands-on technical foundation in SQL and Python sufficient to set architectural direction, review your team's work critically, and remain credible in deep technical discussions. This role requi
- Experience with modern cloud data platforms and pipeline orchestration, and with migrating legacy analytics estates onto governed, paved-path platforms.
- Proven track record building AI/GenAI or agentic capabilities that automate data operations like validation, quality monitoring, root-cause analysis, or insight generation.
- Demonstrated ability to define metrics that shape business strategy and to influence Director- and VP-level stakeholders without direct authority.
- Experience owning a multi-million-dollar impact portfolio, including building the financial case and reporting against it in executive forums.
- Excellent communication skills, with the ability to translate complex technical and data-governance concepts into clear narratives that drive executive decisions.
Nice to have
- Experience with data governance and compliance regimes (e.g., IRS 7216, GDPR, CCPA) and with implementing fine-grained access control at scale.
- Background in semantic layers, knowledge graphs, or knowledge-layer design for AI/agent consumption.
- Experimentation and causal inference depth (A/B testing at scale, difference-in-differences, propensity methods, synthetic control).
- Experience in Customer Success, customer experience, contact center, or FinTech analytics domains.
- Track record of standing up cross-functional governance mechanisms like schema/event registries, data stewardship roles, or change-notification processes for downstream consumers.
Full description
Join the Intuit Customer Success Data Science & Analytics team as the Manager 3 leading Data Foundations. This team builds the governed, compliant data foundation that Intuit's Customer Success analytics and AI capabilities are built on. Metric definitions, clean domain entities, customer journey data products, semantic knowledge layer and the agentic tooling that keeps them healthy. You will lead a team of senior and staff-level data scientists accountable for building the Governed Data Foundation for ICS. This is a hands-on-adjacent people-leadership role. You will set technical direction, own the roadmap and its financial case, grow domain owners, and influence at the Director and VP level. The work spans two halves that must hold together: building data capabilities (consuming models, automating pipeline development and root-cause analysis, generating insights) and building the knowledge layer (understanding the data deeply enough that governed definitions and semantics can be trusted by downstream agents).This role is for someone who thrives in ambiguity, sets standards that outlast individual projects, and builds both systems and people that scale across teams and business units.
Responsibilities
Team Leadership & Talent
- Lead, coach, and grow a team of senior, staff, and principal data scientists; develop domain leads capable of owning a data domain end to end, from source instrumentation through consumption.
- Own hiring, onboarding, performance management, calibration, and promotion advocacy for the team; build and maintain a strong talent pipeline and participate actively in A4A and talent assessment forums.
- Support craft progression across the team and raise the technical bar through review standards, documented best practices, and internal forums.
- Scale yourself through delegation and clear ownership boundaries; role-model an inclusive, high-trust environment that encourages constructive debate.
Strategy & Business Outcomes
- Own the strategic vision, roadmap, success criteria, and financial case for the Data Foundations portfolio, partner with Finance and TPM to quantify and defend impact.
- Develop KPI frameworks that set direction across the organization, applying a 'define once, calculate uniformly' metric standardization model across core data domains.
- Apply first-principles thinking to translate Customer Success business strategy into analytical and data-architecture problems at the Business Unit level.
- Combine insights, business acumen, and industry benchmarks to influence cross-functional leaders, represent the team's work in executive forums and organization-wide reviews.
Data Foundations & Governance
- Drive a shift-left approach to data quality by embedding data design into the product development lifecycle so defects are prevented at source rather than cleaned downstream.