Data Science Intern: ML & AI for Mobility Innovation

Faurecia; Louisville (KY); Hybrid; USD 8,900 - 13,000; Full time

Benefits offered by this job

Health Plan

Wellness program

Tuition Reimbursement

Financial rewards

Job summary

Faurecia is seeking a year-round Data Science Intern for its headquarters, with an opportunity to design, build, and test machine learning models using Python and popular frameworks. You’ll collaborate with cross-functional teams on practical AI solutions and contribute to end-to-end ML workflows while staying current with new trends.

The role focuses on gaining hands-on experience in data analysis, model development, and reproducibility, with emphasis on collaboration and continuous learning in

Qualifications

• Enrolled in a Bachelor’s or Master’s degree program.
• GPA minimum 2.8.
• Data analysis and Excel skills are a plus.
• Majors in computer science, data analysis, or related field.

Responsibilities

• Assist in designing, building, and testing ML models for use cases like computer vision and predictive maintenance.
• Support end-to-end ML workflows, including data preprocessing and feature engineering.
• Collaborate with engineering, manufacturing, and business teams to apply data insights.
• Help optimize model performance and experiment with different algorithms under guidance.
• Use Python and ML frameworks to develop and test models.
• Assist in integrating models into applications and workflows.

Skills

Data analysis

Excel

Python

ML concepts

Education

Bachelor's or Master's in CS/Data Science

Graduation year 2027 or later

Tools

PyTorch

TensorFlow

scikit-learn

Job description

Faurecia is seeking a year-round Data Science Intern for its headquarters, with an opportunity to design, build, and test machine learning models using Python and popular frameworks. You’ll collaborate with cross-functional teams on practical AI solutions and contribute to end-to-end ML workflows while staying current with new trends.

The role focuses on gaining hands-on experience in data analysis, model development, and reproducibility, with emphasis on collaboration and continuous learning in