Data Science Intern (Hybrid, 6 Months)

Job Overview

For more than 75 years TE Connectivity has partnered with customers to produce highly reliable connectors and sensors that power a connected world. Our innovations enable electric vehicles aircraft digital factories smart homes medical devices and next-generation communication infrastructure.

The Singapore R&D Center collaborates with CTOs across TEs Business Units to drive advanced technologies that impact global markets. As part of TEs Digitalization strategy we are investing in simulation modeling and AI-driven data capabilities to accelerate New Product Development and enable first-time-right engineering.

We are looking for a Data Science Intern with strong programming skills and interest in Generative AI and Agentic AI applied to real-world engineering and product design problems.

Job Responsibilities

• Develop data science and AI solutions to support engineering design material development and manufacturing processes
• Apply machine learning and statistical methods to analyze experimental simulation and production data
• Design and prototype AI/agentic systems to automate engineering workflows decision support and knowledge retrieval
• Work with structured semi-structured and unstructured data (including engineering data images and text)
• Perform exploratory data analysis (EDA) to identify patterns anomalies and optimization opportunities
• Develop predictive models (regression classification clustering) for engineering applications
• Collaborate with cross-functional teams including material science manufacturing and product engineering
• Ensure data quality through validation preprocessing and robust pipeline development

Job Requirements

Required:

• Currently pursuing a degree in Data Science Computer Engineering Computer Science AI Statistics Mathematics Engineering or related fields
• Strong programming skills in Python (NumPy Pandas scikit-learn)
• Understanding of machine learning fundamentals and data analysis techniques
• Familiarity with engineering data (simulation experimental or manufacturing data is a plus)
• Experience with version control (Git/GitHub/GitLab)
• Strong analytical thinking and problem-solving skills
• Good communication and teamwork skills

Preferred:

• Exposure to Generative AI or LLMs with focus on practical applications
• Familiarity with agentic AI frameworks (e.g. LangChain LlamaIndex) or workflow automation
• Experience with deep learning frameworks (PyTorch TensorFlow)
• Knowledge of RAG embeddings or data integration techniques
• Experience in computer vision or engineering-related analytics
• Understanding of statistical inference hypothesis testing and experimental design

What Youll Gain:

• Hands-on experience applying AI (including agentic systems) to real engineeringand product design challenges
• Exposure to advanced R&D in materials manufacturing and digital engineering
• Mentorship from experienced scientists and engineers
• Opportunity to contribute to TEs digital transformation and innovation initiatives

Competencies