International Head of AI Strategy and Operationalization

Job Title:  International Head of AI Strategy and Operationalization

Corporate Title: Executive Director

Department: Group Technology

Location: Singapore

Licensed Role: No

Department Overview:

The Artificial Intelligence (AI) Centre of Excellence (CoE) is a dedicated, multi-disciplinary team that advises, builds, and scales AI solutions across Nomura's International Business. Acting as both the strategic engine and delivery arm for AI adoption, the AI CoE drives the responsible development and productionisation of AI capabilities — ensuring every initiative is aligned to business strategy, delivers measurable return on investment, and meets regulatory compliance standards.

Role Overview:

As the International Head of AI Strategy and Operationalisation (Executive Director) within the AI CoE, you will be responsible for facilitating and executing the firm's AI Strategy and the successful adoption of AI solutions for Nomura's International Business - this role combines strategic innovation and leadership with hands on AI delivery implementation. 

You will partner and collaborate with senior stakeholders across business lines and functions to shape the AI strategy, prioritise high impact initiatives, and oversee their progression from concept through to production.  The role requires a deep understanding of AI and emerging technologies, combined with a thorough understanding of what it takes to deploy them safely, compliantly, and sustainably within a global financial services institution.  You will be accountable for unlocking commercial value, strengthening operational efficiency, and enhancing risk management while ensuring alignment with governance standards.   

Role Description:

Strategic Leadership & Vision

• Define and execute the AI strategy – in alignment with global and regional priorities.
• Collaborate with business stakeholders to ideate and identify high-value AI use cases and opportunities – across both business lines and functions, balancing innovation with trust, governance, and regulatory expectations.
• Shape the AI portfolio and contribute to the global AI use case portfolio and capability / product strategy.
• Operate as a thought leader, ensuring industry best practice.

Innovation & Ideation

• Lead ideation workshops, design sessions, and discovery engagements with business stakeholders to explore the art of the possible with AI.
• Drive the incubation of new AI projects - that leverage GenAI, ML, NLP, predictive models, and agentic workflows.
• Stay ahead of technology trends, market dynamics, regulatory developments (regional and local), and competitive activity.

Execution & Delivery

• Oversee the full lifecycle of AI initiatives—from concept, experimentation, prototyping, and PoC/MVP builds through to production deployment and adoption – including the governance process.
• Lead and collaborate with cross functional teams to drive AI initiatives, including data scientists, engineers, subject matter experts.  Act as the bridge between the technical and non-technical stakeholders.
• Develop strategic roadmaps, project plans, timelines, milestones and success metrics.
• Develop patterns, reusable components, enterprise architecture, and best practices.

AI Governance, Risk & Control

• Ensure all AI initiatives meet internal AI governance, risk management, model validation, and regulatory requirements
• Manage responsible AI processes, including documentation, testing, monitoring, transparency, and post-deployment controls – where required.
• Support the implementation of global AI governance frameworks and provide feedback on gaps, risks, and enhancements.

Stakeholder Engagement & Influence

• Build strong relationships with senior leadership across different business lines and functions.
• Act as a trusted advisor and collaborate on AI strategy, adoption, and execution for senior stakeholders.
• Represent the organisation in industry forums, conferences, regulatory engagements, and ecosystem partnerships.
• Leverage relationships with fintechs, third parties, and industry bodies to support the AI Strategy
• Ensure consistent messaging and coordination across internal teams.

Capability Building & Operating Model

• Develop AI capabilities, including talent, processes, training, and culture uplift (e.g., AI literacy, upskilling, innovation programmes).
• Drive adoption of reusable components, and common frameworks to ensure scale, consistency, and reduced time-to-market.
• Partner with HR, Learning, and Data/Tech leadership on skills development, role definition, and workforce transformation.
• Lead education programmes and campaigns to increase AI maturity and capability

Skills, experience, qualifications, and knowledge required:

• 14+ years experience in AI, data science, digital transformation, technology strategy, data strategy within financial services – from either a consulting background or in house strategy team
• Proven experience working within a financial services institution, with exposure to front office business lines and/or corporate functions such as Risk, Compliance, Finance or Operations.   
• Proven track record of taking AI solutions from ideation through PoC to production in a global organisation.
• Experience engaging with regulators and participating in regulatory consultations
• Strong understanding of GenAI, LLMs, and agentic systems
• Understanding of AI governance frameworks, processes, and regulatory frameworks.
• Demonstrated ability to engage and influence senior stakeholders, translating complex AI concepts into business value and practical roadmaps.
• Experience collaborating with cross-functional teams across regions and building AI capabilities that scale.
• Ability to work in a fast-paced environment, with a focus on delivering high-quality results in a timely manner.
• Experience in handling ambiguity and uncertainty, with the ability to navigate complex situations and make informed decisions
• Understanding of how to manage the regulatory landscape in a global organisation.
• Excellent communication and presentation skills, with the ability to communicate complex ideas in a clear and concise manner (written and verbal) – must have strong MS Powerpoint and MS Excel skills
• Ability to think strategically and develop innovative solutions
• Strong understanding of data and AI concepts such as data management, data governance, AI risks etc.
• Passion for learning and growing in the field of data and AI
• Advanced degree in Computer Science, Data Science, AI, Engineering, and/or MBA with strong technical literacy.