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Chicago, IL

Internship

Hybrid

Intern

Grainger is a broad-line distributor serving customers through products, solutions, technology, and customer relationships. The Data Science Intern will analyze digital customer behavior, develop models and experiments, and translate findings into recommendations that improve digital and enterprise customer experiences. The role partners with analytics, product, technology, and business stakeholders and presents insights to technology leaders.

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Responsibilities

Analyze customer experience across digital channels to uncover opportunities to create value for Grainger and our customers
Work with senior analytics team members and business stakeholders to understand business needs and scope projects
Gather, clean, explore, aggregate, and analyze data from large digital and business data ecosystems
Build models, automation, tooling or AI agents for analytics that make insights easier for stakeholders to understand and act upon
Use tools and platforms such as Snowflake, Power BI, Excel, Adobe Analytics, SQL, Python, R, and AI-enabled productivity tools when appropriate
Summarize insights, implications, limitations, and tradeoffs for both technical and non-technical audiences
Partner closely with current team members on ongoing activities such as ad hoc analysis, A/B testing, troubleshooting, and measurement planning
Learn how a modern analytics team operates and how data influences digital products, customer experience, and technology decisions
Demonstrate ownership, curiosity, adaptability, and critical thinking while contributing as part of the team
Present your work, impact, and key learnings to technology leaders at the end of the internship

Qualification

Required

Currently pursuing a degree in quantitative fields such as Data Science, Statistics, Mathematics, Engineering, Analytics, Operations Research, Economics, Computer Science, or a related field
Expected graduation with a bachelor's degree between December 2026 and June 2027; current enrollment in a Masters program is preferred
Evidence of self-directed learning, project work, case competitions, internships, coursework, or other experiences using data to solve problems
General knowledge of analytics, statistics, or data science and the curiosity to explore large data ecosystems in a business context with an interest in digital customer behavior and customer experience measurement
Experience coding for data science or analytics applications; Python or R preferred
Experience with statistical modeling or machine learning techniques such as regression, classification, clustering, natural language processing, time-series modeling, or experimentation
Knowledge of database design and logic (e.g. Teradata, Snowflake), with the ability to build queries in SQL or similar query languages
Ability to explain technical decisions, compare approaches, and describe the tradeoffs behind models, tools, or methods
Ability to communicate clearly through written summaries, visualizations, presentations, and stakeholder conversations
Willingness to use AI and analytics tools thoughtfully while validating outputs and explaining assumptions
Strong collaboration skills to effectively work with partners across analytics, product, technology, and business teams
Cumulative GPA of 3.2 or higher
Does not require sponsorship

Preferred

Expected graduation with a bachelor's degree between December 2026 and June 2027; current enrollment in a Masters program is preferred
Experience coding for data science or analytics applications; Python or R preferred

Benefits

Hybrid work location type
10-week, paid program based in our downtown Chicago office
Networking, social, and professional development events
Hands-on exposure to modern technology stacks, digital platforms, AI-enabled workflows, and enterprise systems
Learning from experienced team members
Present the work you accomplished to senior leadership

As a leading business-to-business organization, more than 4.5 million customers worldwide rely on Grainger for products in categories such as safety, material handling and metalworking, along with services like inventory management and technical support.

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