About The Role

Business Function

DBS is accelerating its ambition to be an AI-enabled bank with a heart. We are looking for a senior analytics leader to shape, scale, and industrialise AI-led transformation across the bank.

The incumbent will lead the adoption of AI/ML, Generative AI, and Agentic AI to create measurable business value—enhancing customer experience, unlocking cross-sell and up-sell opportunities, improving productivity, and strengthening fraud and risk management. The role calls for deep analytical expertise, strategic judgement, and the ability to influence senior stakeholders across business, technology, risk, and data.

Key Accountabilities

Business Partnering & Influence

Act as a strategic advisor to senior leadership, translating analytics and AI insights into clear priorities, decisions, and measurable business outcomes.

AI & Analytics Strategy

Define and execute an enterprise analytics strategy that accelerates business growth, sharpens decision-making, and strengthens fraud analytics.

GenAI & Agentic AI Innovation

Lead the design and deployment of Generative AI and Agentic AI solutions that reimagine customer journeys, reduce operational toil, improve productivity, and enable smarter data-led decisions.

Analytics Capability Development

Build a high-impact analytics team by embedding modern tools, reusable frameworks, agile delivery practices, and continuous upskilling in AI, data science, and governance.

Data Architecture & Governance

Work closely with Group Technology and Data Engineering to ensure scalable, secure, and well-governed data pipelines and architecture aligned to the bank’s enterprise data strategy.

Requirements

Technical & Analytical Expertise

Expert-level proficiency in Python and PySpark for large-scale data processing, advanced model development, and automation.
Demonstrated success in taking GenAI and Agentic AI use cases from concept to production, with clear value realisation.
Strong understanding of data architecture, data pipelines, MLOps, and model deployment frameworks in enterprise environments.

Banking & Business Acumen

Deep knowledge of retail and institutional banking products, customer lifecycles, economics, and profitability levers.
Proven ability to lead data-led transformation and deliver commercial, customer, risk, and productivity outcomes in banking or financial services.

Leadership & Stakeholder Skills

Exceptional stakeholder management, influencing, storytelling, and executive communication skills.
Track record of building, inspiring, and developing high-performing analytics and AI teams.

Qualifications

Postgraduate qualification in Data Science, Computer Science, Statistics, Engineering, or a related quantitative discipline.
15+ years of experience in data analytics, AI, or digital transformation, ideally in banking or financial services.
Hands-on exposure to enterprise-scale AI/ML production deployments, responsible AI practices, and AI governance frameworks.