About the job
Intuit is seeking an experienced Data Science leader to manage our People Analytics Data Science & Research team at Intuit. Our team partners closely with Intuit's HR leaders, COEs, Finance, and business partners to deliver data-driven insights that shape our people strategies and elevate decision-making across the company. We are looking for an experienced People Analytics Data Science Leader to set analytical direction across workforce forecasting, employee research and listening, talent and mobility analytics, and the AI-native tools that put insight directly in leaders' hands. The portfolio spans predictive modeling, psychometric research, and applied AI, and it continues to evolve. This leader will lead a distributed analytics team and will be accountable for the rigor of the work before it reaches executive audiences.
Responsibilities
Set analytical and modeling direction across workforce forecasting and organizational effectiveness, Voice of Employee research, and AI-native tooling, ensuring consistency and rigor across all domains.
Apply first-principles thinking to turn People & Places strategy into analytical problems at the function level, and propose and lead the initiatives that follow from it.
Connect insights across hiring, workforce planning, performance, internal mobility, and employee experience to surface patterns and trade-offs only visible at the portfolio level, and translate them into decision-ready leadership recommendations.
Co-create the analytics strategy for AI-native decision tools in partnership with cross-functional teams, drawing on industry developments, strategic insight, and domain knowledge.
Guide the data science behind workforce planning and organizational effectiveness measures, ensuring the models leaders rely on are sound and consistently applied.
Lead a distributed team of data scientists and researchers, deepening both technical craft and the influence that turns analysis into decisions.
Qualifications
Minimum
10+ years in people analytics, with deep data science and applied research experience in a people or workforce context.
4+ years of experience managing analytics or data science teams.
Demonstrated depth in predictive and prescriptive modeling, experimentation, and causal inference, sufficient to review and improve others' methodological choices rather than only interpret their conclusions.
Fluency in SQL and Python or R, with comfort in modern cloud data environments and data workflow management tooling.
Experience across workforce domains such as headcount forecasting, attrition and retention modeling, hiring funnel analytics, compensation, or organizational effectiveness, and with survey and psychometric research methods.
Experience building or measuring AI-native analytics products, with a clear point of view on how to evaluate them and how model performance connects to business outcomes.
Proven experience establishing shared data definitions and reporting standards across functions with competing sources of truth.
Demonstrated ability to influence senior executives through storytelling, translating complex analysis into a narrative that changes a decision rather than describing a situation.
Track record of building feedback loops into analytics work, so the team knows what changed as a result and invests accordingly.
Preferred
Experience managing a multi-team or multi-domain organization strongly preferred.