Job Description

WHO WE ARE:

As Singapore’s longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.

Today, we’re on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia’s leading financial services partner for a sustainable future.

We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career.

Your Opportunity Starts Here.

Enterprise Knowledge Management Specialist

ROLE

We are seeking an Enterprise Knowledge Management Specialist within the Data & AI function to establish, operationalize and scale the Bank's Enterprise Knowledge Management Capability.

This role will partner closely with Group Risk Management (GRM), Business Functions, Technology, Compliance, HR and Operations to define enterprise knowledge governance standards, operating models, taxonomy, controls and AI-ready knowledge practices.

Business functions remain accountable for the ownership, accuracy and maintenance of their respective knowledge assets. This role will act as the framework architect, enterprise catalyst and implementation partner - developing the strategy, implementation roadmap, standards, playbooks, governance mechanisms and adoption approach required to bring the framework into practical execution across the Bank.

This role reports directly to Head, Group Data Office.

KEY RESPONSIBILITIES

Enterprise Knowledge Strategy & Operating Model

• Partner with GRM to define and implement the Bank's enterprise knowledge management strategy, roadmap and operating model.
• Position knowledge as a governed enterprise asset supporting productivity, operational resilience, compliance and AI effectiveness.
• Develop practical implementation plans to move from fragmented repositories to trusted, reusable and AI-ready enterprise knowledge.
• Establish business cases, value measures and adoption plans for prioritized knowledge domains.

Knowledge Governance Framework

• Partner with GRM and enterprise stakeholders to establish knowledge governance standards, policies, controls and implementation playbooks.
• Define roles and responsibilities across knowledge owners, stewards, custodians, users and governance forums.
• Design lifecycle management processes covering knowledge creation, review, approval, publication, consumption, refresh, retention and retirement.
• Develop review cadences, quality criteria, certification standards and escalation routines for critical knowledge assets.

Framework Implementation & Change Execution

• Lead phased implementation across priority business and support functions, starting with high-value domains.
• Translate the framework into practical working routines, templates, control checkpoints, training and adoption materials.
• Coordinate cross-functional execution across Risk, Technology, Compliance, Operations, HR and business domain teams.
• Drive change management and behavioural adoption without replacing business ownership of content.

Taxonomy, Metadata & Information Architecture

• Develop enterprise taxonomy, metadata and classification standards for knowledge assets.
• Define standards for ownership, authoritative source identification, versioning, confidentiality, effective date, review date and content status.
• Improve discoverability and reusability of policy, process, control, risk, product, operational and technical knowledge.
• Establish information architecture principles for structured and unstructured knowledge repositories.

AI-Ready Knowledge Foundation

• Define standards for AI-consumable and AI-trustworthy knowledge assets supporting Microsoft Copilot, Enterprise Search, RAG, Knowledge Graphs and AI Agents.
• Partner with Data, AI and Technology teams to improve retrieval quality, grounding accuracy, source traceability and user trust.
• Establish criteria for content certification, knowledge freshness, trust scoring, Identify authoritative knowledge sources and support controls to reduce duplication, outdated content and hallucination risk.

Measurement & Continuous Improvement

• Define KPIs, maturity assessments and dashboards for knowledge quality, adoption, search success, freshness, duplication and AI readiness.
• Monitor implementation progress and continuously refine standards based on business feedback, audit observations and emerging AI capabilities.
• Support senior management updates on value realization, risk reduction and enterprise adoption outcomes.

REQUIREMENTS

Experience & Qualifications

• Bachelor's or master's degree in Information Management, Data Management, Computer Science, Information Systems, Business, Risk Management or related fields.
• 10+ years of experience in enterprise data governance, information management, knowledge management, enterprise architecture, AI governance, digital transformation or related roles.
• Experience in banking or financial services is highly preferred.
• Proven experience establishing enterprise governance frameworks and driving organization-wide implementation and adoption.
• Demonstrated ability to translate strategy into executable roadmaps, playbooks, operating routines and measurable outcomes.

Knowledge, Data & AI Expertise

• Strong understanding of knowledge lifecycle management, taxonomy, ontology, metadata, information architecture and content governance.
• Familiarity with data governance, AI governance and risk/control operating models in regulated environments.
• Good understanding of Microsoft Copilot, Enterprise Search, RAG architectures, knowledge graphs, semantic indexing, vector databases and AI agents.
• Ability to define AI-ready knowledge standards, authoritative source strategies and trust mechanisms for enterprise AI use cases.

Leadership & Stakeholder Skills

• Strong stakeholder management across Risk, Compliance, Technology, Operations, HR and business functions.
• Ability to influence without direct authority and drive alignment across senior stakeholders and domain owners.
• Excellent communication skills, with the ability to explain complex governance and AI-readiness concepts in business language.
• Strong execution mindset: able to move from framework design to practical implementation, adoption and measurable business value.

What we offer:

Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry-leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.