About this role
Learning Outcomes
- Gain an understanding of the LNG value chain, Terminal Operations, Singapore's electricity market and energy trading.
- Learn machine learning and optimisation models on real LNG and power market data, and see how models shape planning decisions for a critical part of Singapore's energy infrastructure.
- Develop automated data pipelines and production-grade software using industry engineering practices.
- Explore how LLMs and AI workflows are used in real analytics and engineering projects.
- Turn analysis into business insights and present them to management and cross-functional teams.
- Strengthen teamwork, problem-solving skills and an innovative mindset in a fast-paced environment.
Requirements
- Undergraduate or graduate in Computer Science, Data Science or a related field.
- Proficiency in Python and JavaScript; knowledge of Java, Kotlin or Swift is an advantage.
- Able to understand, structure and explain all submitted code, including code produced with AI-assisted tools.
- Demonstrate strong ability in data analysis and visualisation, and communicate findings clearly and accurately.
- Organise projects and code in a structured and maintainable manner.
- Possess a basic understanding of LLMs and related workflows; experience developing automated data pipelines is an advantage.
- Demonstrate a proactive, can-do attitude and strong attention to detail, and work effectively both independently and as part of a team.
- Students who can commit minimum 5-6 months.