AVP/VP, Investment Research, Private Equity, Technology Investment Group

VPPrivate EquityTechnologyFull-time
Location

San Francisco, United States

Date Posted

May 22, 2026

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About This Role

GIC is one of the world's largest sovereign wealth funds, managing over $2,000 employees across 11 global locations and investing in more than 40 countries. The Technology Investment Group (TIG) within GIC Private Equity invests across the lifecycle of technology companies, deploying capital in growth-stage private and public companies while also serving as a limited partner in top-tier technology funds.

TIG maintains a global presence across San Francisco and Mumbai, with a portfolio that includes category-leading technology companies such as Anthropic, Stripe, Databricks, Affirm, DoorDash, Ramp, Figma, and Grafana. The team incubated GIC's Bridge Forum, a proprietary business development platform connecting innovative tech companies with traditional industry stakeholders.

The AVP/VP, Investment Research role sits at the center of TIG's investment lifecycle. The successful candidate will lead the team's research efforts using advanced analytics, statistical methods, and AI/LLMs to drive investment decisions and maintain a differentiated market view. This is not a traditional research support role — the position functions as a core partner on investment decisions, collaborating directly with deal teams to stress-test investment theses and address key concerns.

Key responsibilities include partnering with deal teams to deliver differentiated investment insights, validating core underwriting assumptions, and driving investment decisions through a rigorous quantitative approach. The candidate will develop innovative solutions leveraging data and AI to generate differentiated signals that directly influence investment decisions, and engage directly with prospective technology companies alongside the deal team during due diligence.

GIC is looking for candidates with strong quantitative and analytical skills, experience with data science or AI tools, and a genuine interest in technology investing. The lean team structure provides significant responsibility and direct exposure to the full investment lifecycle from sourcing through execution.

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