AVP/VP, Data Scientist - Audit Analytics & AI Enablement, Internal Audit Department, Asia Pacific

The Internal Audit Department, Asia Pacific Division (IADAP) at SMBC is responsible for providing independent assurance over the adequacy and effectiveness of internal control systems, governance, risk management, and compliance across the Asia Pacific and India Divisions.

This role sits within the IADAP Planning Group – Digital Innovation & Enablement team. The purpose of this role is to design, develop, and embed data analytics and AI‑enabled solutions into Internal Audit activities, to enhance audit coverage, efficiency, and quality through robust, repeatable, and regulator‑defensible use of data and analytics. The role supports risk-based auditing and continuous auditing across the Asia Pacific and India Divisions.

This role operates as a specialist enablement function within IADAP. Accountability for audit judgements, conclusions, and opinions remains with the respective audit teams and engagement leads.

Job Responsibilities

• Design, build, and maintain reusable audit analytics and AI‑enabled routines to support audit planning, testing, issue identification, and reporting across financial, operational, and regulatory audits, producing reliable and audit‑defensible evidence.
• Design, build, and maintain data analytics and AI‑enabled routines for department‑wide enablement, including internal office automation, audit risk assessment processes, and stakeholder reporting, ensuring solutions are robust, reusable, and appropriate for audit and management use.
• Perform data extraction, preparation, and validation, including reconciliation, completeness and accuracy checks, and logic validation, to ensure the robustness, reliability, and explainability of analytics and AI outputs.
• Partner with audit teams throughout the audit lifecycle, from planning through reporting, to translate audit objectives into analytics‑enabled testing approaches and to support interpretation of results.
• Collaborate with data owners and IT stakeholders to understand data availability, data flows, and system constraints, enabling effective and appropriate use of enterprise data and approved analytics and AI tools.
• Support continuous auditing and continuous monitoring initiatives by developing analytics and AI‑enabled routines that evolve audit testing from point‑in‑time reviews to periodic or ongoing control checks, indicators, dashboards, and exception reporting.
• Drive analytics and AI capability uplift across IADAP through mentoring, structured training, documentation, and “train‑the‑trainer” knowledge transfer, ensuring consistent, secure, and regulator‑appropriate adoption.
• Ensure analytics and AI‑enabled routines are developed and used in accordance with Internal Audit methodology, data governance standards, model risk considerations, and approved AI usage guidelines, with appropriate documentation and explainability.
• Participate in regional and global data analytics and AI initiatives, contributing to standardisation, scaling of use cases, and alignment with group audit methodologies and governance expectations.
• Support audit methodology enhancement and process improvement initiatives by leveraging automation, analytics, and AI to improve audit efficiency, consistency, and documentation quality.

Job Requirements

• Experience
  • Essential: 5–10 years of relevant experience in data analytics, audit analytics, risk management, financial services, or technology functions, preferably within regulated environments. Practical experience applying analytics to financial, operational, or regulatory processes to support audit or risk assessment activities.
  • Desirable: Experience delivering or supporting AI‑enabled or advanced analytics use cases in audit, risk, or compliance contexts. Exposure to business and/or technology‑enabled audits.
• Qualifications
  • Essential: Recognised degree in Computer Science, Data Science, Mathematics, Financial Engineering, or a related quantitative or technology discipline.
  • Desirable: Professional certifications such as CIA, CISA, CAMS, or equivalent. Formal training or certification in data analytics, automation, or AI‑related disciplines.
• Functional Competencies
  • Strong analytical and problem‑solving skills, with the ability to translate audit objectives into robust analytics or AI‑supported solutions.
  • Hands‑on experience with data analytics, visualisation, and advanced data manipulation tools (e.g. Python, Power BI, Tableau, Databricks or equivalent).
  • Sound understanding of internal audit methodology, risk‑based auditing, and audit evidence requirements.
  • Awareness of data reliability, validation, and IT application control considerations relevant to audit work.
• Leadership Competencies
  • Ability to operate effectively in a transformation‑driven environment with a proactive and delivery‑focused mindset.
  • Demonstrates ownership, discipline, and the ability to work independently while supporting audit teams to achieve objectives.
  • Applies sound judgement and professional scepticism when analysing issues and interpreting analytics or AI outputs.
  • Builds trust and credibility with auditors, stakeholders, and technology partners.
• Personal Attributes
• • Strong written and verbal communication skills in English.
  • Detail‑oriented, disciplined, and quality‑focused, with the ability to work independently with minimal supervision.
  • Curious, adaptable, and committed to continuous learning and capability uplift.
  • Team‑oriented, with the ability to engage constructively across functions and regions.