Business Analyst Intern

Grainger Businesses•Allouez, WI

3d•Hybrid

About The Position

As a Business Analytics Intern at Imperial Supplies, we’ll help you design an experience that meets your learning objectives while giving you hands-on exposure to how analytics supports real business decisions. You will work closely with experienced analytics professionals and business stakeholders to transform data into actionable insights that drive sales, margin improvement, and operational efficiency. Imperial Supplies is a growing distributor of fleet maintenance products, headquartered in Green Bay since 1958, with a strong history of double-digit annual growth. This internship provides an opportunity to contribute to meaningful analytics initiatives while building practical skills in reporting, modeling, and stakeholder communication. Under general supervision, the Business Analytics Intern will support analytics and reporting initiatives by gathering business requirements, developing dashboards and analytical models, and presenting insights to stakeholders. This role blends elements of business analysis and data science, providing exposure to both descriptive reporting and advanced analytics.

Requirements

Current enrollment in a degree program related to Business Analytics, Data Analytics, Data Science, or a similar quantitative field
Foundational knowledge of data analysis concepts and business problem-solving
Experience or coursework using Excel
Strong analytical curiosity with attention to detail
Ability to manage multiple priorities and work in a collaborative, fast-paced environment
Effective written and verbal communication skills

Nice To Haves

Exposure to Power BI, SQL, and/or Python preferred

Responsibilities

Partner with business stakeholders to gather insight requirements, define deliverables, and estimate level of effort for analytics initiatives.
Design, build, test, and maintain reports and dashboards in Power BI to support recurring monitoring of key metrics.
Develop and validate analytical models using Python and SQL to support business decision-making and optimization efforts.
Perform data collection, validation, and analysis from internal or third-party data sources to ensure accuracy and usability of outputs.
Translate complex analytical findings into clear, actionable insights and present results to business stakeholders at varying levels.
Document requirements, assumptions, and business value associated with analytics deliverables.
Support continuous improvement efforts by identifying opportunities to automate manual reporting and improve existing dashboards or analytics processes.