Description

Temasek is a global investment company headquartered in Singapore, with a net portfolio value of S$434 billion (US$324 billion, €299 billion, £250 billion, and RMB2.35 trillion) as at 31 March 2025. Marking our unlisted assets to market would provide S$35 billion of value uplift and bring our mark to market net portfolio value to S$469 billion.

Our Purpose So Every Generation Prospers guides us to make a difference for today's and future generations.

Operating on commercial principles, we seek to deliver 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 2025, please visit www.temasekreview.com.sg .
For Sustainability Report 2025, please visit https://www.temasek.com.sg/content/dam/temasek-corporate/sustainability/2025/Temasek-Sustainability-Report-2025.pdf .

Responsibilities

Automation, AI & GenAI Adoption

• Support the adoption of Generative AI and LLMs for research synthesis and preparation of briefing materials for senior management.
• Build and implement automation for key inputs and outputs, including input file preparation and standard diagnostics, as well as automated output analysis and comparisons.
• Work with Technology/Data teams and vendors to implement and embed automation and AI solutions into day-to-day workflows.

Support projection of long-term expected returns for Temasek's portfolio

• Support the annual expected return projection cycle by preparing input datasets/files and running standard outputs.
• Perform checks and diagnostics on expected return and risk outputs, including attribution, volatility-related analysis, and scenario comparisons.
• Support preparation and updating of materials for senior management forums

Requirements

• Bachelor's degree in a quantitative discipline such as Finance, Economics, Statistics, Engineering, Computer Science, or Business Analytics.
• 1-4 years of relevant experience or internships/projects in analytics, modelling, automation, or data work; exposure to finance or macro topics is helpful.
• Strong Excel modelling skills and comfort working with large datasets.
• Hands-on exposure to Generative AI tools and basic automation capabilities such as Python, Power Query, or RPA tools.
• Strong ownership, attention to detail, and ability to coordinate across stakeholders.