Data Analytics & Engineering Intern, Performance Analytics

Temasek is a global investment company headquartered in Singapore, with a net portfolio value of S$518 billion (US$401b, €350b, £304b, RMB2.77t) as at 31 March 2026. Our Purpose So Every Generation Prospers guides us to make a difference for today's and future generations. We seek to build a resilient and forward-looking portfolio that will deliver good sustainable returns over the long term.    
 
We have 13 offices in 9 countries around the world: Beijing, Hanoi, Mumbai, Shanghai, Shenzhen, and Singapore in Asia; and Brussels, London, Mexico City, New York, Paris, San Francisco, and Washington, DC outside Asia. 
 
For more information on Temasek, please visit www.temasek.com.sg    
For Temasek Review 2026, please visit www.temasekreview.com.sg
For Sustainability Report 2026, please visit www.temasek.com.sg/SR2026

• Implement and help build research and tracking platforms, incorporating data pipelines, analytics engines and visualization tools.  Architect and design data pipeline infrastructure to facilitate data ETL processes, and query financial data from a variety of data sources
• Work with internal and external tech teams to manage and operationalize these platform
• Maintain / design our in-house databases to fulfill the needs of the various analytics workstreams / products
• Explore and develop ways/containers to house analytics engines to facilitate workflows.
• Identify and implement improvements to automate manual processes, optimize speed, efficiency, and scalability
• Set up / maintain version control for the analytics codebase
• Help with research on analytics projects which would include studying industry trends and financial markets, correlating different exogenous variables to performance. 

• Able to commit full-time for a minimum of 20 weeks. Interns who are able to commit to a full-time (5 days/week) or a minimum of part-time (4 days/week) internship is strongly preferred. 
• Bachelor degree in Computer Science, Engineering, Business or related fields.
• Proficiency in Python, R, and SQL
• Experience with AWS, S3, JFrog, Kubernetes preferred
• Experience with QlikSense, Snowflake, Tableau, and Git preferred but not required
• Understanding of portfolio theory, statistics, financial modeling, and traditional financial performance metrics would be helpful but not required
• Proficiency in Microsoft Word, Excel, and PowerPoint