People Analytics & AI Intern (Summer 2027)

Clarios•Milwaukee, WI

3d•Hybrid

About The Position

This internship focuses on supporting the design, development, and testing of People Analytics solutions. The intern will contribute to key projects such as workforce and turnover reporting, talent acquisition analytics, executive scorecards, and integrated HR dashboards. A significant part of the role involves assisting with AI-enabled analytics prototypes, including natural-language data exploration, visualization, and research-assistant capabilities. The intern will also help improve data quality, documentation, repeatability, and governance across various HR data sources and tools.

Requirements

Currently enrolled as a full-time student at an accredited U.S. college or university.
Pursuing an undergraduate degree in Data Analytics, Computer Science, Information Systems, Business Analytics, Human Resources, Industrial/Organizational Psychology, or a related field.
Foundational experience with data analysis and visualization.
Exposure to Excel plus one or more of Python, SQL, Power BI, Streamlit, or similar tools is preferred.
Curiosity about people analytics and responsible AI.
Strong problem-solving skills.
Attention to detail.
Communication skills.
Willingness to validate results rather than accept outputs at face value.
Ability to be in the greater Milwaukee area in the summer.
Must be authorized to work for any employer in the US without the need for sponsorship, now or in the future.

Responsibilities

Support the design, development, and testing of People Analytics solutions.
Contribute to priority projects like workforce and turnover reporting, talent acquisition analytics, executive scorecards, and integrated HR dashboards.
Assist with AI-enabled analytics prototypes, including natural-language data exploration, visualization, and research-assistant capabilities.
Help improve data quality, documentation, repeatability, and governance across Workday, Snowflake, Streamlit, Power BI, Excel, and related HR data sources.
Partner closely with the HR Data and Analytics Lead and stakeholders across HR Technology, HR, IT, and the business to clarify questions, requirements, and success measures.
Profile, clean, reconcile, and validate data; build calculations and visualizations; and document assumptions, source logic, testing results, and limitations.
Use Python, SQL, Excel, and business intelligence tools to develop analyses and prototypes, applying AI responsibly while protecting confidential employee information.
Communicate findings through concise dashboards, written summaries, evidence trails, and presentations.
Incorporate stakeholder feedback through an iterative approach.