Associate/AVP, Quantitative Strategist, Private Equity

Associate/AVP, Quantitative Strategist, Private Equity

Location: Singapore, SG

Job Function: Private Equity

Job Type: Permanent

GIC is one of the world’s largest sovereign wealth funds. With over 2,000 employees across 11 offices around the world, we invest in more than 40 countries globally across asset classes and businesses. Working at GIC gives you exposure to an extraordinary network of the world’s industry leaders. As a leading global long-term investor, we Work at the Point of Impact for Singapore’s financial future, and the communities we invest in worldwide.

GIC Private Equity (PE) GIC is a global investment firm and has one of the largest and broadest private equity programmes amongst all institutions. GIC PE invests across the Americas, Europe and the Asia-Pacific in a range of sectors including Healthcare, Consumer, Financial services, Technology, Industrials, Sustainable Energy and Infrastructure. Besides investing through private equity fund managers, GIC PE also invests across the capital structure in equity, senior and junior debt, in secondary PE deals, restructuring & opportunistic credit and special situations. We currently have over 100 active relationships with fund managers and have invested directly in more than 1000 companies globally across multiple sectors.

What will you do in the role?

As a Quantitative Strategist in Private Equity, you willharness GIC’s wealth of internal and external data across both public and private markets to extract transformative insights and accelerate GIC’s ability to spot and seize differentiating opportunities. Spearhead the integration and adoption of AI across GIC to elevate investment processes, reap operational efficiencies, as well as to discover insights. Champion the application of quantitative research and analysis to enhance and institutionalize investment analysis and decision-making.

In this role, you willfocus onquantitative research, data-driven insights, and GenAI innovationthat directly enhance investment decision-making and portfolio performance. You will have the opportunity to work on a wide range of projects, collaborate with cross-functional teams and leverage cutting-edge technologies. We are looking for individuals who possess strong analytical and problem-solving skills, a passion for AI and quantitative analysis, and a keen interest or knowledge in Private Equity or related investment domains.

What will you do in this role?

• Generate Differentiated Investment Insights - Leverage data, analytics, and AI to identify risks, opportunities, and differentiated insights that enhance investment decision-making.
• Partner with Deal Teams Across the Investment Lifecycle - Work closely with deal teams to shape investment theses, evaluate opportunities, and support portfolio monitoring through analytics and data-driven insights.
• Build Scalable Analytics & AI Solutions - Develop reusable tools, models, and data products that can be applied across deals, sectors, and portfolio companies.
• Rapid Prototyping & Experimentation - Quickly prototype new analytical approaches, AI applications, and decision-support tools to test high-impact use cases with investment teams.
• Leverage Alternative & Proprietary Data - Identify and utilize alternative data sources to enhance investment insights and create differentiated perspectives.
• Drive Data-Driven Investment Culture - Act as a thought partner to deal teams to promote the use of analytics and AI in investment processes.
• Portfolio & Thematic Analysis - Conduct cross-portfolio and thematic analysis to identify trends, risks, and opportunities across investments.
• Collaborate Across Functions - Work with technology, data, and other Strats to build scalable capabilities and share best practices.

What qualifications, skills and traits should you possess in this role?

• Academic degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Finance, or related fields, with experience in data science or quantitative research.
• Hands-on experience with generative AI technologies (e.g., OpenAI, Anthropic, Hugging Face, or similar frameworks).
• Hands-on experience with Databricks for data engineering, analytics, and model deployment.
• Strong understanding of large language models (LLMs), prompt engineering, and retrieval-augmented generation (RAG).
• Proficiency in Python and SQL; familiarity with cloud-based AI platforms (AWS, Azure, GCP) and vector databases (e.g., OpenSearch, Pinecone, FAISS) is a plus.
• Experience working with diverse data sources, including structured and unstructured text data.
• Strong analytical and problem-solving skills, with the ability to combine GenAI insights with quantitative reaso