TE Connectivity Hiring! Full Time Data Science Intern - AI - Engineering Analytics (Hybrid, minimum 5 Months) in - Ricebowl

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