Manager 3, Data Science - Data Foundations

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. Establish governed clean entities, standardized metric layers, and semantic/knowledge layers as the trusted source of truth for Customer Success data domains. Own end-to-end customer journey data products, stitching behavioral clickstream, contact touchpoints, and time-series journeys to pinpoint drop-offs and high-contact moments that drive cost-to-serve. Lead compliance and security execution for the organization's data estate by field-level access control, data-access management, and PII minimization against enterprise mandates and hard regulatory deadlines. Negotiate and maintain clear ownership boundaries with Data Engineering and PD partners on governed base tables, paved-path platforms, and the graduation of analyst-built assets into managed ownership. AI Capabilities & Automation Lead custom implementations of AI/GenAI capabilities for key business initiatives, in partnership with AI and platform teams. Direct the build-out of agentic data tooling for improving productivity and automation like pipeline migration and development agents, automated data-quality detection, and automated root-cause analysis targeting material reductions in d