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 TE's Business Units to drive advanced technologies that impact global markets. As part of TE's 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 You'll Gain:
- Hands-on experience applying AI (including agentic systems) to real engineering and product design challenges
- Exposure to advanced R&D in materials, manufacturing, and digital engineering
- Mentorship from experienced scientists and engineers
- Opportunity to contribute to TE's digital transformation and innovation initiatives
