Data Science Intern, Digital Experience Analytics

W. W. Grainger; Chicago, Northern (IL, KY); Hybrid; USD 38,000 - 53,000; Full time

Benefits offered by this job

Paid internship

Networking events

Professional development

Job summary

W. W. Grainger, Inc.

invites applications for a 10-week Data Science Internship in our downtown Chicago office. You will work across teams including Product Engineering, Cybersecurity, Applied ML, and Digital Experience Analytics to build data-driven solutions that support real customer outcomes. You will model, analyze, and interpret data, gain exposure to modern stacks and AI-enabled workflows, and present insights to senior technology leaders at summer's end.

Qualifications

• Pursuing a degree in Data Science, Statistics, Mathematics, Engineering, Analytics, OR Economics or CS.
• Experience with data problems and projects demonstrating analytical thinking.
• Programming experience in Python or R.

Responsibilities

• Analyze customer experiences across digital channels to uncover value opportunities.
• Collaborate with analytics, product, technology, and business stakeholders to frame questions.
• Gather, clean, explore, and analyze data from large digital and business ecosystems.
• Build models, automation, or AI tooling to make insights actionable for stakeholders.
• Summarize insights and communicate implications to technical and non-technical audiences.
• Work on ad hoc analyses, A/B tests, and measurement planning with teammates.

Skills

Python

R

SQL

Snowflake

Power BI

Excel

Adobe Analytics

AI tools

Education

Data Science or quantitative degree

Expected graduation Dec 2026–Jun 2027

Tools

Snowflake

Power BI

Adobe Analytics

Excel

Job description

W. W. Grainger, Inc.

invites applications for a 10-week Data Science Internship in our downtown Chicago office. You will work across teams including Product Engineering, Cybersecurity, Applied ML, and Digital Experience Analytics to build data-driven solutions that support real customer outcomes. You will model, analyze, and interpret data, gain exposure to modern stacks and AI-enabled workflows, and present insights to senior technology leaders at summer's end.