AVP, Data Analyst, Infrastructure

GIC is one of the world’s largest sovereign wealth funds. With over 2,000 employees across 11 locations 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.

Infrastructure We deploy long-term capital through direct, and fund investments across the capital structure to diversify our portfolio.

Portfolio Performance & Data Analytics, Infrastructure PPDA provides data-driven analytics that support investment and asset management decisions across GIC's infrastructure business.

What impact can you make in this role? Turn institutional knowledge across our infrastructure investments into the data and tools used to underwrite new deals, manage capital more efficiently, and support value creation across our portfolio.

Success in this role is measured by the quality and reliability of the data and tools you deliver, and by the investment and asset management decisions they support.

What will you do in this role?

• Partner with business teams to identify KPIs, trends, opportunities, and areas for improvement: work closely with Deal Teams, asset management, and internal technology teams to identify valuable data sources and translate business needs into well-scoped data solutions.
• Build and maintain dashboards, reports, and data models to surface actionable insights: conduct business analysis and assessments (e.g. performance reviews, opportunity sizing, process/efficiency evaluation).
• Improve ways of working: apply data management best practices and improve internal processes by evaluating new tools, platforms, and capabilities such as but not limited to: data ontologies, graph databases, and agentic workflows.
• Extract, clean, transform, and model data from multiple sources using Databricks, SQL, and related tooling: design, implement, and maintain pipelines that ingest, clean, structure, label, and store both structured and unstructured private markets infrastructure data.
• Maintain data quality and governance: monitor data issues, investigate root causes, and design and track resolutions, reconciling data across systems and sources to maintain integrity, lineage, and governance standards.
• Translate for the business: engage business users and non-technical stakeholders to gather requirements, explain trade-offs in plain language, and ensure solutions are fit for purpose, including supporting user acceptance testing of data and system changes.

What qualifications, skills and traits should you possess?

• Bachelors degree in quantitative discipline (e.g. Computer Science, Mathematics, Engineering, or a related field), with around 5 years of hands-on experience working with data in an enterprise setting.
• Databricks in an enterprise setting: demonstrated, hands-on experience building and operating on Databricks at scale, with a strong grasp of lakehouse architecture, data lineage, data quality, and governance.
• Strong technical skills: high proficiency in Python and SQL, and working knowledge of modern data-processing libraries such as Pandas, Polars, and DuckDB.
• Applied ML / LLM experience: practical experience applying machine learning and large language models to support data processing, information extraction, and modelling workflows.
• Effective communication: able to work with business users and non-technical stakeholders, translating technical concepts into clear business terms and working well across diverse teams.
• Curiosity about the buy side: a genuine interest in learning about private market infrastructure investments and asset management. A finance or investment background is not required — the willingness and aptitude to learn the domain is what