About the role
Associate-level role focused on leveraging alternative data and AI to generate differentiated investment insights for Temasek's global portfolio. The position bridges investment teams and data science groups, applying advanced analytics to fundamental research across single stocks, sectors, and macro themes.
InvestmentOnsite
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, strengthen conviction, and improve the quality and speed of investment decision-making
- 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
- Design and refine AI-native workflows that improve how investors source information, analyze companies, test hypotheses, and synthesize insights
- Engage external suppliers and service 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