Strategic Projects Intern: Data Analytics & AI for Manufacturing

Daimler AG; Charleston (SC); On-site; USD 23,000 - 32,000; Full time

Benefits offered by this job

Onsite position

Competitive hourly wage

Job summary

Mercedes-Benz Vans, LLC MBV Charleston is offering an internship in Operations Engineering focused on factory planning and project execution. The intern will support planning, scheduling and reporting for a multi-million dollar plant expansion project.

Preferred candidates are recent graduates or current students in construction management, engineering, data analytics or related fields, with advanced Excel and Power BI skills and an interest in AI and digital transformation within manufacturing.

Qualifications

• Pursuing or recently graduated in Construction Management, Mechanical/Civil Engineering, Project Management, Data Analytics or related field.
• Strong proficiency in Microsoft Excel and Power BI.
• Interest in AI, automation, data analytics, and digital transformation within manufacturing.

Responsibilities

• Assist planning, scheduling and execution of brownfield construction and engineering projects for plant transformation.
• Track milestones, budgets, risks, issues and dependencies for accurate project controls.
• Collaborate with Engineering, Plant Planning and Production to translate requirements into actionable plans.
• Develop and maintain project schedules, critical-path analyses and executive status reports.
• Create and maintain advanced Excel models and Power BI dashboards for project reporting.
• Create automated reporting workflows and leverage AI tools to improve team efficiency.

Skills

Project KPI Tracking

Advanced Excel

Power BI

Risk management

AI: Co-Pilot workflows

Education

Bachelor’s or Master’s Degree in Construction Management or Engineering

Tools

Microsoft Co-Pilot

Job description

Mercedes-Benz Vans, LLC MBV Charleston is offering an internship in Operations Engineering focused on factory planning and project execution. The intern will support planning, scheduling and reporting for a multi-million dollar plant expansion project.

Preferred candidates are recent graduates or current students in construction management, engineering, data analytics or related fields, with advanced Excel and Power BI skills and an interest in AI and digital transformation within manufacturing.