Sr. Manager, Analytics; Research & Data Science

Intuit is seeking an experienced Data Science leader to manage our People Analytics Data Science & Research team  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.

This is a leadership role for someone who has not stopped being a scientist: you will develop the team and you will personally review model design, challenge assumptions and interpretability, and hold the methodological bar. This role is critical to supporting Intuit's ongoing organizational transformation, ensuring that how we plan, organize, and develop our workforce is scalable, insight-driven, and aligned to our mission of powering prosperity for our people and the company.

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.
• 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.

• 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.

• 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…