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.
Combine insights, business acumen, and industry-wide learnings to influence VP-level and above stakeholders, and stand behind a recommendation under scrutiny.
Partner with P&P COEs, the HRBP community, and Finance leadership to resolve workforce-data definitional questions, including how hires and headcount are defined and reconciled, and represent that work credibly with senior stakeholders.
Strategy and Measurement for AI-Native Experiences
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.
Help design strategic frameworks and success measurement across key People & Places initiatives, including AI-powered work.
Guide teams toward the data sets, insights, and methodological approaches that improve model outcomes, bringing in both external and internal sources.
Influence the analytics product roadmap so the portfolio continues to improve insight and decision-making across the employee lifecycle.
Inference and Algorithms
Guide the data science behind workforce planning and organizational effectiveness measures, ensuring the models leaders rely on are sound and consistently applied.
Review and challenge the team's models with accountability for assumptions, bias, and interpretability, guiding teams from ambiguous business questions to end-to-end analytical solutions.
Build, review, and scale advanced predictive and prescriptive models, applying rigor across experimentation and causal inference.
Identify new methodologies and external trends and adapt them to People & Places use cases, creating shareable frameworks that clarify when and how a new approach should be used.
Act as a thought partner on build versus buy decisions for analytics workflow tooling, identifying the pain points worth solving.
Leadership
Lead a distributed team of data scientists and researchers, deepening both technical craft and the influence that turns analysis into decisions.
Set a clear vision for the team, build a high-performance culture, and drive winning results.
Own intake and demand management with P&P and business partners, shaping requests into clearly defined deliverables and outcomes.
Build feedback loops into how the team works, tracking whether analysis changed a decision and using that to steer where the team invests next.
Establish how the team works: standards for methodology review, documentation, and handoff, so quality does not depend on who happens to pick up the work.
Qualifications
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; experience managing a multi-team or multi-domain organization strongly preferred.
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.
Passion for enabling data-driven, equitable people processes that foster growth and inclusion.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Mountain View $234,000 - $316,500
