People Analytics Intern

People Analytics Internship (Summer 2027) — People Success

This is a 12-week internship during summer 2027. You will join the People Analytics team within our People Success Function. This team provides intelligence and tools that empower leaders to make key people decisions and drive business value. You will support analyses across the employee lifecycle, help streamline reporting processes, and contribute to solutions that measure the impact of complex People programs.

What You’ll Do

• Analyze People data across the employee lifecycle to identify trends and surface actionable insights for leadership
• Apply AI tools to accelerate data exploration and enable self-service access to insights for stakeholders
• Prototype AI-driven workflow automations for recurring reports, anomaly detection, and data-quality checks
• Support ad hoc data requests by building and maintaining spreadsheets and dashboards
• Partner with stakeholders to improve dashboard navigation, access, and self-service reporting
• Collaborate with team members to develop executive presentations that translate data into clear narratives

Required Skills and Experience

• Currently pursuing a degree or certificate in an analytical discipline (e.g., data science, statistics, I/O psychology, business analytics, or a related field)
• Demonstrated experience analyzing and manipulating data using spreadsheets (Excel, Google Sheets), with the ability to translate findings into actionable recommendations
• Proven ability to communicate data insights clearly in both written and verbal formats to non-technical audiences
• Track record of handling highly sensitive or confidential data with discretion
• Familiarity with at least one data visualization tool (Looker, Tableau, Power BI, or OneModel) or basic SQL knowledge is a plus
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality

Position Details

• Position ID: P78055
• Work style: Remote-first (quarterly in-person “surges”)