GTG Intern - Data Science

Grainger Businesses•Chicago, IL

1d•Hybrid

About The Position

The Grainger Technology Group (GTG) internship is a 10-week, paid program based in our downtown Chicago office where interns work across teams such as Product Engineering, Cybersecurity, Applied Machine Learning User Experience, Digital Experience Analytics, and more to help build the technology that keeps Grainger and its customers moving. As a GTG intern, you will be treated as a member of the team and contribute to meaningful work tied to real customer and business outcomes, not a separate side project. You will gain hands-on exposure to modern technology stacks, digital platforms, AI-enabled workflows, and enterprise systems while learning from experienced team members. Throughout the summer, you will also participate in networking, social, and professional development events and present the work you accomplished to senior leadership. As a Data Science Intern on the Digital Experience Analytics team, you will use statistics, modeling, experimentation, and data storytelling to help Grainger better understand digital customer behavior and improve customer-facing and enterprise digital experiences. You will partner with analytics, product, technology, and business stakeholders to frame questions, evaluate data, develop models or analyses, and translate findings into recommendations that can guide decisions. This role is ideal for someone who enjoys solving ambiguous problems, exploring large datasets, and connecting technical analysis to business impact. You will gain exposure to modern data platforms, statistical and machine learning techniques, digital analytics tools, and AI-enabled workflows while learning how data science influences product and customer experience decisions at scale.

Requirements

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.

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.