Data Science Intern – AI for Manufacturing Innovation

Nissan Motor Iberica SA; Smyrna (TN); On-site; USD 21,000 - 30,000; Full time

Job summary

Nissan is seeking a Data Science Intern to join our Smyrna, TN team for a 12-week full-time program. You will work with AI technologies and data analytics to improve manufacturing performance and throughput, applying data-driven decision making to optimize operations in a world-class automotive environment.

You'll develop AI-powered tools, analyze downtime, support CMMS enhancements, and collaborate with engineering, maintenance, and production to drive continuous improvement.

Qualifications

• Currently enrolled in an undergraduate or graduate degree in data science, CS, AI, ML, IS, or related field.
• Junior, Senior, or Master’s students starting the upcoming term.
• Strong interest in AI, analytics and manufacturing technologies.
• Experience with Python, SQL, C++ or similar.
• Strong analytical and problem-solving abilities.
• GPA of 3.0 or higher and willingness to provide transcripts during application.

Responsibilities

• Develop AI-powered tools to improve manufacturing efficiency and performance.
• Support root cause analysis using data analytics and AI to resolve process issues.
• Analyze downtime and performance data to identify improvements.
• Assist CMMS enhancements and related reporting tools.
• Collaborate with engineering, maintenance, and production to drive data-driven improvement.

Skills

Python

SQL

C++

Data analysis

Problem solving

GPA 3.0

Communication

Education

Data Science

Computer Science

Artificial Intelligence

Machine Learning

Information Systems

Computer Engineering

Tools

CMMS

SCADA

Job description

Nissan is seeking a Data Science Intern to join our Smyrna, TN team for a 12-week full-time program. You will work with AI technologies and data analytics to improve manufacturing performance and throughput, applying data-driven decision making to optimize operations in a world-class automotive environment.

You'll develop AI-powered tools, analyze downtime, support CMMS enhancements, and collaborate with engineering, maintenance, and production to drive continuous improvement.