LNG & Energy Analytics Intern (ML & Data Pipelines)

Singapore LNG Corporation Pte Ltd; Singapore; On-site; SGD 13,000 - 22,000; Full time

Job summary

Singapore LNG Corporation Pte Ltd invites applicants for a 5-6 month internship focusing on data science, analytics, and production-grade data pipelines. You will work on LNG and energy market datasets, build and explain models, and present findings to cross-functional teams.

Ideal candidates are pursuing CS/Data Science degrees, can structure code, understand AI-assisted tools, and show strong communication, attention to detail, and collaboration in a dynamic energy environment.

Qualifications

• Must be pursuing undergraduate or graduate studies in Computer Science, Data Science or a related field.
• Ability to understand, structure and explain code, including AI-assisted code.
• Strong data analysis and visualization skills with clear, accurate communication.

Responsibilities

• Understand LNG value chain, terminal operations, and Singapore's electricity market.
• Study ML and optimisation models on LNG and power market data.
• Develop automated data pipelines and production-grade software following industry practices.
• Explore how LLMs and AI workflows are used in analytics projects.
• Turn analyses into business insights and present to management and cross-functional teams.
• Demonstrate teamwork and problem-solving in a fast-paced environment.

Skills

Data analysis

Data visualization

Teamwork

Attention to detail

Independent work

Proactive attitude

Education

CS/DS student or related field

Job description

Singapore LNG Corporation Pte Ltd invites applicants for a 5-6 month internship focusing on data science, analytics, and production-grade data pipelines. You will work on LNG and energy market datasets, build and explain models, and present findings to cross-functional teams.

Ideal candidates are pursuing CS/Data Science degrees, can structure code, understand AI-assisted tools, and show strong communication, attention to detail, and collaboration in a dynamic energy environment.