Reliability Analytics Intern: Data-Driven Impact

Daimler Truck North America LLC.; Fort Mill (SC); Hybrid; USD 29,000 - 40,000; Full time

Benefits offered by this job

Professional development events

Housing & transportation stipend

Resume reviews/mock interviews

Employee resource groups

Company social events

Event ticket offerings

Job summary

Daimler Truck North America LLC is seeking a Reliability Engineering Intern in Fort Mill, SC to support data analysis across warranty, reliability and engineering domains. You will identify trends, deliver insights, and contribute to initiatives that improve product quality and profitability.

The role involves working with cross-functional teams and real-world datasets, with a hybrid schedule combining in-office and remote work.

Qualifications

• Must be currently enrolled in a Bachelor’s program or recent graduate within 1 year.
• Pursuing a quantitative field such as Engineering, Science, Statistics, Economics, or Data Analytics.
• Strong oral and written communication skills; ability to work in teams.

Responsibilities

• Analyze data from multiple sources (dealers, customers, technicians) to identify trends and root causes.
• Support development of summary reports and dashboards to communicate findings.
• Utilize analytics tools for forecasting, trend analysis and cost-driver identification (parts, labor).
• Assist in evaluating cost exposure and reliability data to inform risk assessment and portfolio optimization.
• Help identify outliers in repair activity and develop tools to detect opportunities or risks.

Skills

Data analysis

Excel

PowerPoint

Tableau/Power BI

SQL

R or Python

Communication

Team collaboration

Education

Bachelor’s in Engineering/Science/Statistics/Data Analytics

Tools

HANA

Snowflake

Tableau

Power BI

Job description

Daimler Truck North America LLC is seeking a Reliability Engineering Intern in Fort Mill, SC to support data analysis across warranty, reliability and engineering domains. You will identify trends, deliver insights, and contribute to initiatives that improve product quality and profitability.

The role involves working with cross-functional teams and real-world datasets, with a hybrid schedule combining in-office and remote work.