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Keppel

[Keppel Internship Programme 2027] Intern, Data/AI Engineering (Jan - May 2027)

Singapore

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hirly's read of this role

Seniority
Internship
Country
SG
Work mode
On-site / unstated
First seen by hirly
27 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

JOB DESCRIPTION

Keppel is a leading global asset manager and operator with strong capabilities in energy & environment, urban development and connectivity, creating solutions for a sustainable future.

  • The intern will be responsible in the following:
  • 'Build & Maintain Data Pipelines
  • Support AI/ML Model Development & Deployment
  • Contribute to Data Platform & AI/Agentic Solutions
  • Learning Outcomes:
  • 'Understand how large-scale data platforms and architectures are designed
  • Learn best practices in data security, access control, and responsible AI usage
  • Develop practical experience contributing to production-grade data/AI solutions in a business context
  • Gain hands-on experience in building and managing end-to-end data pipelines
  • Develop strong understanding of data modeling, data quality checks, and transformation techniques
  • Become proficient in working with modern data stack tools (e.g., SQL, Python, cloud data platforms like AWS/Snowflake)

JOB REQUIREMENTS

1. Educational Background & Technical Foundations

  • Pursuing a degree in Computer Science, Data Science, Engineering, or a related field
  • Strong fundamentals in programming (preferably Python) and SQL
  • Basic understanding of data structures, algorithms, and software engineering principles

2. Data & AI Knowledge

  • Familiarity with data processing concepts (ETL/ELT, data modeling, data cleaning)
  • Exposure to machine learning fundamentals (e.g., supervised/unsupervised learning, model evaluation)
  • Experience with common data/ML libraries (e.g., Pandas, NumPy, scikit-learn) is a plus

3. Tools & Platform Exposure

  • Exposure to cloud platforms (e.g., AWS, Azure, or GCP) and modern data ecosystems is advantageous
  • Familiarity with databases (SQL/NoSQL) and data warehousing concepts (e.g., Snowflake, BigQuery, Databricks)

4. Problem-Solving & Mindset

  • Strong analytical thinking and problem-solving skills
  • Ability to break down complex problems into structured solutions
  • Eagerness to learn and adapt in a fast-paced, technology-driven environment

5. Communication & Collaboration

  • Good communication skills, with the ability to explain technical concepts clearly
  • Team player with a proactive and ownership-driven attitude
  • Ability to work with cross-functional teams (analytics, business stakeholders)

BUSINESS SEGMENT

Corporate

PLATFORM

Operating Division

Original posting on Keppel's site ↗

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