About the role
Job Summary
Join our Internal Audit Data Analytics team as a Lead Data Scientist and help shape the future of data-driven auditing. With 6–9 years of experience, you will design and maintain scalable data solutions, ensure compliance with global data regulations (including GDPR), and empower auditors/inspectors with high-quality data and advanced analytics. You will master all the datasets of the perimeter assigned to you, becoming the point of contact for all Internal Audit. This is a strategic role offering exposure to cutting-edge technologies, global collaboration, and the opportunity to influence audit practices across the organization.
Key Responsibilities
• Design, build, and optimize secure, scalable data solutions for audit use cases.
• Support global audit and inspection missions with scalable data extractions, advanced data analytics, automation solutions etc. with python and relevant technologies• Collaborate with audit teams and CDOs to understand data needs and deliver compliant, high-quality data to internal audit.
• Translate complex audit requirements into scalable analytical use cases, including full-population testing, advanced exploratory analytics , anomaly detection , etc.
• Ensure data solutions align with global privacy regulations, including GDPR.
• Develop interactive dashboards and reports in Power BI to visualize audit analytics/metrics
• Continuously improve data accessibility and quality to support audit missions.
• Stay up to date with emerging data engineering tools, AI capabilities, and audit trends.
• Document solutions , architectures, data processes, reusable components• Identify relevant internal APIs for data extraction, assess their suitability, and implement/maintain reusable Python packages to leverage such APIs to accelerate data access.
• Design and support AI use cases using Azure-based capabilities, ensuring appropriate governance, traceability, security, and scalability.