Head of People Analytics & AI-Driven Insights

Intuit Inc.; San Diego (CA); On-site; USD 234,000 - 317,000; Full time

Job summary

Intuit Inc. is seeking an experienced Data Science leader to direct the People Analytics Data Science & Research team in Mountain View.

You will partner with HR, COEs, Finance, and business units to deliver data-driven insights shaping people strategies and executive decision-making. The role demands hands-on scientific leadership, building the team, reviewing model design for rigor and interpretability, and guiding the analytics roadmap across workforce forecasting, employee research, and

Qualifications

• 10+ years in people analytics with research experience.
• 4+ years leading analytics or data science teams.
• Proficient in SQL and Python or R.
• Experience with predictive and prescriptive modeling, experiments, and causal inference.
• Ability to influence senior executives through storytelling.
• Experience building AI-native analytics products.
• Experience establishing shared data definitions and reporting standards.

Responsibilities

• Set analytical and modeling direction across forecasting and research.
• Lead initiatives from first-principles to analytic solutions.
• Translate portfolio insights into decision-ready recommendations.
• Influence senior stakeholders with data-driven insights.
• Collaborate with HR, Finance, and COEs to resolve workforce data definitions.
• Lead a distributed team of data scientists and researchers.
• Establish standards for methodology, documentation, and handoff.

Skills

People analytics leadership

Executive stakeholder management

Predictive modeling

Prescriptive modeling

SQL

Python or R

Data-driven decision making

Job description

Intuit Inc. is seeking an experienced Data Science leader to direct the People Analytics Data Science & Research team in Mountain View.

You will partner with HR, COEs, Finance, and business units to deliver data-driven insights shaping people strategies and executive decision-making. The role demands hands-on scientific leadership, building the team, reviewing model design for rigor and interpretability, and guiding the analytics roadmap across workforce forecasting, employee research, and