About the role
AI summarisedThis is an Associate-level Investment Researcher role at Temasek, a global investment company. The role involves applying AI and advanced analytics to fundamental research, using alternative data to generate investment insights, and bridging investment teams with data science teams.
BusinessFull-time
Key Responsibilities
- Apply AI and advanced analytics to fundamental research and investment decisions
- Work closely with investment teams to frame and answer investment-relevant questions through the use of alternative data, AI-enabled research techniques, and advanced analytical methods
- Translate investment questions into practical analytical approaches, identifying the most relevant datasets and tools, and generating insights that can inform company, sector, and market views
- Support fundamental research, strengthening conviction, and improving the quality and speed of investment decision-making
- Drive AI-centric research workflows and dataset application
- Develop a deep understanding of individual datasets, including where they are most useful, how they should be interpreted, and the limitations and trade-offs associated with each
- Help design and refine AI-native workflows that improve how investors source information, analyze companies, test hypotheses, and synthesize insights
- Partner with external data suppliers and solution providers on data sourcing, dataset evaluation, and related analytical applications
- Assess the relevance, quality, and practical usability of external datasets, and help ensure they are deployed effectively in support of investment research objectives
Requirements
- Minimum 2 years of relevant experience, preferably in private equity, public equities, equity research, investment research, investment banking, corporate finance, or management consulting
- Strong foundation in corporate finance and accounting
- Demonstrated experience in financial statement analysis, returns analysis, valuation analysis, and company and industry research
- Strong research and analytical skills, with the ability to connect data-driven work directly to an investment thesis and to core underwriting questions
- AI-native mindset with familiarity across a range of AI tools, workflows, and use cases, including a clear understanding of their strengths, limitations, and trade-offs
- Ability to apply AI and advanced analytics in a practical manner to improve research efficiency, insight generation, hypothesis testing, and investment decision support
- Experience working with alternative data sources is preferred; experience applying such data in an investing context would be a strong advantage
- Strong written and verbal communication skills, with the ability to communicate analytical insights clearly and influence investment discussions
- Working knowledge of Python and SQL is preferred, though the primary emphasis is on analytical judgment, research application, and effective use of AI-enabled workflows
- Strong interpersonal skills and the ability to build trust and credibility with investment teams, data science partners, and external providers
- Ability to work independently, navigate ambiguity, and rapidly build understanding across new companies, sectors, and datasets