Industrial Engineering Intern — Data & Analytics

UPS Supply Chain Solutions, Inc.; United States; Presencial; USD 28 000 - 34 000; Tempo parcial

Resumo da oferta

UPS Supply Chain Solutions, Inc. offers an analytics-focused internship in industrial engineering. You will build models and visualizations to drive insights, working with cross-functional teams to evaluate processes and recommend improvements within the UPS network.

The role emphasizes hands-on learning, exposure to AI/automation, and the opportunity to influence operational efficiency through data-driven storytelling and engineering collaboration.

Qualificações

• Knowledge of industrial engineering and 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 across business units
• Excellent written, oral, and interpersonal skills

Responsabilidades

• Develops analytical models and data visualizations to drive analytic insights.
• Interacts with cross-functional teams to model current operations processes and evaluate potential solutions.
• Presents data insights and recommendations to key stakeholders utilizing process improvement analysis
• Exploring and applying AI, automation, and data analytics tools to improve operational efficiency and support engineering initiatives

Conhecimentos

Industrial engineering

Statistics

Research

Communication

Collaboration

Interdepartmental communication

Interpersonal skills

Formação académica

Pursuing degreed program

Descrição da oferta de emprego

UPS Supply Chain Solutions, Inc. offers an analytics-focused internship in industrial engineering. You will build models and visualizations to drive insights, working with cross-functional teams to evaluate processes and recommend improvements within the UPS network.

The role emphasizes hands-on learning, exposure to AI/automation, and the opportunity to influence operational efficiency through data-driven storytelling and engineering collaboration.