ED/SVP, Regional CBG (Retail) Data Chapter Lead, Transformation and Data, Group COO

DBS · Singapore

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Role Summary

As a Regional CBG (Retail) Data Chapter Lead, you will be responsible for the end-to-end data, analytics, and AI ecosystem. Operating at the intersection of business strategy and deep technical execution, you will provide thought leadership to uncover new value pools using advanced data capabilities. You will lead a diverse team of data professionals, including Data Scientists, Data Translators, and Business/Data Analysts, ensuring they have the tools, skills, and strategic direction to build, operate, and scale business-critical solutions.

Job Responsibilities

Drive Business Outcome from Data Analytics

• Partner with CBG leadership to identify opportunities where analytics can create significant business impact.
• Develop analytics strategy and capability to maximize impact from AI/ML, including Gen AI and Agentic AI.
• Provide guidance in managing and prioritizing Data Analytics workstreams and backlogs.
• Drive use of data and AI in sustainable, responsible way.

Build & Operate (Build & Run)

• Accountable for the end-to-end execution and full lifecycle of all data products, from build and deployment to maintain and continuously improve.
• Partner with technology stakeholders to ensure scalable and resilient data & analytics pipelines.
• Support AI Industrialization and increase adoption of DBS AI Protocol and data science reusable assets to reduce time to value.
• Drive reduced effort for end-to-end deployment of data assets by supporting the creation and usage of reusable components (data, compute, models, monitoring) across the AI Lifecycle.
• Drive best practices and knowledge sharing across analytics use cases, experimentation, and nudges.

Talent & Chapter Leadership

• Shape and implement a strong employee value proposition to attract, retain, and develop Data Analytics Talent, supporting employee value proposition workstreams.
• Develop skills and deepen expertise of data analytics talent through building expertise, best practices & standards, and providing technical direction.
• Establish a strong and vibrant community of highly engaged data professionals.
• Lead, mentor, and develop a diverse chapter of data scientists, data translators, and data/business analysts into a world-class team.
• Manage performance, career progression, and strategic allocation of chapter members into delivery squads based on skills and prioritized initiatives.

Governance, Risk & Compliance

• Ensure all AI/GenAI models comply with internal policies, such as AI Governance Standards.
• Champion data quality and data governance protocols to safeguard sensitive data.

Job Requirements

Experience & Domain Knowledge

• 15+ years of experience in data science and analytics, with at least 3+ years in a senior leadership role.
• Graduate / Post-graduate Degree preferably in a science or finance related discipline.
• Demonstrated success in taking advanced AI products from ideation to production at an enterprise scale.
• Strong business experience in financial services, preferably banking, with several years in managing data analytics / AI products delivery.
• Strong banking domain knowledge, ideally in institutional banking or banking operations.

Technical Acumen

• Familiar with data analytics tools, techniques, industry trends, and developments.
• Well-versed with data analytics techniques like predictive, prescriptive, ML, and AI, including Generative/Agentic AI.
• Deep conceptual and practical understanding of modern AI architectures, agentic workflows, and traditional machine learning algorithms.
• Familiar with modern data stacks, cloud platforms, and MLOps principles.

Leadership & Soft Skills

• Strong leadership and senior stakeholder management skills.
• Ability to navigate complex environments to achieve technical and business outcomes.
• Passion for problem-solving and a "can-do" attitude.
• Strong interpersonal and relationship-building skills.
• Exceptional communication and presentation skills, with the ability to demystify complex concepts for non-technical senior executives.
• Tolerance for ambiguity and a relentless drive to challenge the status quo, pushing toward a data-first culture.

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