Audit Analyst Data Scientist

Leverages advanced data analytics, automation, artificial intelligence (AI), and emerging technologies to enhance audit effectiveness, efficiency, and risk coverage. Designs and develops analytics solutions that support audit planning, testing, continuous monitoring, and reporting. Analyzes large volumes of structured and unstructured data to identify risks, anomalies, trends, and control weaknesses. Collaborates with audit teams, business partners, and technology stakeholders to deliver data-driven insights that strengthen risk management, governance, and regulatory compliance.

Key Accountabilities:

Develops and executes data analytics, automation, and AI-enabled solutions to support all phases of the audit lifecycle, including planning, fieldwork, reporting, and issue validation.

Performs data extraction, transformation, and analysis from multiple internal systems to identify risk indicators, control exceptions, and operational inefficiencies.

Designs and maintains audit dashboards, monitoring tools, and repeatable analytics that enhance audit coverage and productivity.

Applies statistical techniques, machine learning, and advanced analytical methods to detect anomalies, emerging risks, and trends across business processes.

Evaluates and implements innovative technologies and analytical approaches to improve audit testing, continuous auditing, and assurance activities.

Partners with audit teams and stakeholders to understand audit objectives and deliver meaningful, data-driven insights and recommendations.

Provides analytical support for regulatory, compliance, operational, technology, cybersecurity, and financial audits.

Translates complex analytical findings into clear and actionable insights for audit management and business stakeholders.

Exercises judgment to identify, assess, and solve complex data and risk-related issues while adhering to audit standards and methodologies.

Works independently on multiple projects, balancing competing priorities and tight timelines.

Supports the development of audit analytics best practices, knowledge sharing, and continuous improvement initiatives across the department.

Takes measured risks while protecting the Bank by applying the Risk Management Framework in the execution of responsibilities, making sound and risk-informed decisions aligned with business strategy, policies, standards, laws, and regulations.

Foundational Level of Proficiency

• Data analytics and visualization
• Artificial Intelligence and Generative AI
• Data governance, privacy, and ethics
• Critical thinking
• Risk and control concepts
• Creative problem solving

Intermediate Level of Proficiency

• Audit methodology and internal controls
• SQL, Python, SAS, R, or other analytical programming languages
• Data extraction, transformation, and validation
• Statistical analysis and machine learning
• Dashboard development (Power BI, Tableau, etc.)
• Data wrangling and data quality assessment
• Automation and process improvement
• Technology and cybersecurity risk concepts
• Analytical reasoning and problem solving
• Written and verbal communication skills
• Stakeholder management and influence skills
• Collaboration and teamwork
• Project management and prioritization
• Risk-based decision making

Experience

• Typically 4-6 years of experience in audit analytics, data analytics, internal audit, risk management, or a related discipline.
• Post-secondary degree in Data Analytics, Computer Science, Information Systems, Statistics, Accounting, Finance, Mathematics, or a related field.
• Experience supporting audits through data analysis, automation, continuous monitoring, or AI-enabled solutions.
• Technical proficiency gained through education and/or practical business experience.

This version aligns more closely with an Internal Audit Analytics & Innovation team supporting Technology, Operations, Cybersecurity, and enterprise audits.