Intern - Manufacturing Engineering - Data Analysis

The Lafayette, IN facility has a position for Manufacturing Engineering Intern. In this position you will be responsible for assisting the Strategy and 6 Sigma group with process improvement projects in areas of manufacturing, assembly, quality, supply chain, and business processes. This department is responsible for implementing connected assets and smart manufacturing solutions as part of a digital strategy.

This position is a 15 to 20 hour per week assignment during the school year with the opportunity to work 40 + hours per week during school breaks and during the summer months. This position can continue until graduation with mutual agreement of the student and manager.

Major Responsibilities:

• Create visual tools for data analysis (dashboards, reports, databases)

• Support projects to connect manufacturing assets and collect process data

• Perform analysis of data using software, statistics, other techniques.

• Serving as a resource member for 6 Sigma teams analyzing and improving processes

• Assist with compiling business performance measures

• Complete independent projects as assigned

Basic Qualifications:

• Currently enrolled as a full-time student in the School of Engineering or Technology (ME, IE, MET or IET, Computer Science, Data Science preferred) with a cumulative GPA of 2.8 or higher.

• Must be enrolled at a college/university in the Lafayette/West Lafayette area to be considered.

• Completed 30 semester hours prior to start of internship.

• If a transfer student, must have 12 semester hours completed at a 4-year university.

• Expected graduation should be May 2027 and beyond.

• Experience using computer-based programs to organize, access, analyze data

• Familiarity with data analysis through statistics, data analytics

• Desire to learn applications related to controls, cloud computing, machine learning

Preferred Skills:

• Knowledge of SQL database querying

• ·Experience using data visualization tools such as PowerBI or Tableau

• ·Understanding of ETL processes