Industrial Engineering Intern - AI & Process Optimization

UPS Supply Chain Solutions, Inc.; Utah; On-site; USD 42,000 - 52,000; Full time

Benefits offered by this job

401(k) retirement program – eligible

Personal time

Discounted Employee Stock Purchase

Job summary

UPS Supply Chain Solutions, Inc. seeks an Industrial Engineering Intern to work on targeted projects with operational observations, data collection, and cross‑functional communication. Projects are presented to the Industrial Engineering staff on completion.

Responsibilities include work measurement in MSD, cost‑benefit analysis, process improvement, operational planning, and applying AI, automation, and data analytics to boost efficiency across engineering initiatives.

Qualifications

• Knowledge of Industrial Engineering and/or Engineering related discipline
• Effective statistical analysis skills
• Effective research and communication skills
• Enthusiasm, idealism, creativity and dedication to getting results
• Ability to work collaboratively and independently
• Ability to interact and communicate effectively across business units
• Excellent written, oral, and interpersonal skills

Responsibilities

• Work Measurement in Master Standard Data (MSD)
• Cost benefit analysis
• Process improvement analysis
• Operational planning
• Exploring and applying Artificial Intelligence (AI), automation, and data analytics tools to improve operational efficiency and support engineering initiatives

Skills

Industrial Engineering

Statistical analysis

Research skills

Communication skills

Teamwork

Cross-functional comms

Interpersonal skills

Education

Industrial Engineering

Job description

UPS Supply Chain Solutions, Inc. seeks an Industrial Engineering Intern to work on targeted projects with operational observations, data collection, and cross‑functional communication. Projects are presented to the Industrial Engineering staff on completion.

Responsibilities include work measurement in MSD, cost‑benefit analysis, process improvement, operational planning, and applying AI, automation, and data analytics to boost efficiency across engineering initiatives.