VP, Data Governance Lead Data Stewardship , Technology Group - GIC PRIVATE LIMITED

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.

Enterprise and Data Technology Enterprise & Data Technology builds and advances the technology that underpins our enterprise and data capabilities. It brings together our core technology and data experts to design and deliver platforms for integration, analytics, and innovation. By combining these strengths into one coordinated group, we create seamless solutions that connect systems, improve data accessibility, and leverage AI at the platform level to enable smarter decision-making. Through modern, scalable, and secure technology, the team empowers the organisation with tools that drive insight, collaboration, and operational excellence.

What impact can you make in this role? The Data Stewardship Lead will play a key role in driving GIC’s enterprise data governance and management initiatives, focusing on unstructured data assets. This role requires a strong blend of technical expertise, business understanding, and leadership to design, implement, and maintain scalable data stewardship processes that ensure data quality, compliance, and usability across the organization.

What will you do as a VP, Data Governance Lead (Data Stewardship)?

Data Classification: Support the development and application of classification standards for unstructured data, ensuring consistency across business lines.

Data Annotation & Labelling: Lead efforts to analyse, identify, and label unstructured data samples accurately, improving recall rates and supporting machine learning and AI initiatives.

Roadmap Development for Unstructured Data Labelling: Develop and drive a strategic roadmap to progressively label, tag, and classify all unstructured data across the firm, ensuring systematic coverage, prioritization, and alignment with enterprise data governance objectives.

Collaboration with Cybersecurity & AI Teams: Partner with cybersecurity engineering and AI teams to enhance algorithm recognition, analyse misclassified data, and contribute to model improvement discussions.

Process Optimization & Platform Enhancement: Continuously refine data annotation operations, optimize label sampling and review mechanisms, and contribute to functional design improvements for the annotation platform.

Stakeholder Collaboration: Work closely with business end-users, data vendors, data engineers, and other stakeholders to implement and support data solutions using best practices and technologies.