Junior Specialist: Analytics & Data Science

We are looking for a passionate, technically gifted candidate to deliver advanced analytics and data science capabilities in support of the Internal Audit function. Through executing data-driven audit procedures — including exceptions testing, full population analysis and control effectiveness assessment — in accordance with the Group Audit Plan and Internal Audit methodology; and to contribute to the design, development and governance of AI-powered audit solutions that enhance the quality, efficiency and insight of the assurance process.

• Secure access to data warehouses and other relevant data sources.
• Manage secure data transfers from business units.
• Create and maintain data dictionaries and reusable datasets for audit use.
• Clean, transform, and prepare data for audit testing.
• Build and maintain reusable, automated audit analytics programs.
• Develop sustainable analytics models, scripts, and dashboards to support audit execution.
• Collaborate with audit teams to design and implement complex, insightful analytics tests.
• Ensure compliance with data security and transfer protocols.
• Contribute to the execution of strategic A.I initiatives within Internal Audit.
• Identify opportunities to embed data science and A.I solutions into audit planning, fieldwork, and reporting.
• Develop and implement data-driven business monitoring programs.
• Research and evaluate emerging analytics tools and techniques relevant to audit.
• Build strong relationships with data owners, business MI teams, and audit stakeholders.
• Act as a trusted advisor to audit teams on analytics opportunities and best practices.
• Communicate progress and insights to Data Analytics Manager and Head of Department.
• Stay current with developments in data analytics, audit, and regulatory trends.
• Share knowledge and tools with peers across Internal Audit.
• Attend relevant conferences and training sessions to enhance skills and awareness.
• Apply analytics across the audit lifecycle: risk assessment, control testing, and outcomes analysis.
• Proactively identify opportunities to improve audit processes through analytics.
• Take initiative on additional tasks and projects that enhance audit value.

• Bachelor’s degree in informatics, Statistics, Computer Science, Actuarial Science, or a related field.
• Minimum of 3 - 5 years’ hands-on experience in data analytics and data science, with a strong focus on coding-based tools. Experience in Applied Machine Learning is an advantage.
• Proven experience in Python, SQL is essential.
• Proficiency in Excel and/or Power BI is expected, but not as primary tools.
• Familiarity with SAS or R is advantageous.
• Experience developing analytics in support of risk, controls, or audit functions.
• Exposure to financial services or regulated industries is preferred.
• Relevant certifications (e.g., SAS, SQL, Python, data mining, machine learning) are advantageous.