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Manager 3, People Analytics (Research & Data Science)

Category Data Location Mountain View, California; San Diego, California Job ID 23671
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Company Overview

Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With tens of millions of customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview

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. 

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

Strategic Thinking and Business Acumen

  • 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.


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
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