The core responsibilities of the Data Analytics Auditor is to:
- Execution of scoped work (as data analyst and/or data scientist)
- Drive advancement and development in the analytics space through defined strategic initiatives
- Act and deliver in accordance with Internal Audit plans, methodologies, policies and procedures
- Able to adapt to change with an agile working environment
- Arrange access to data warehouses and regularly required data sources.
- Arranging the secure receipt of data files from business via multiple channels.
- Creation of a data dictionary including definitions and availability (where appropriate).
- Build and maintain common data sets regularly required by audit delivery teams.
- Assist with data cleaning and preparation for audit delivery teams.
- Build and maintain a library of re-usable automated auditing programmes and functional specifications.
- Develop sustainable and re-useable Data Analytics models, programs and dashboards to improve the efficiency of ABSA Group Internal Audit and to improve audit coverage
- Development of data analytics models and programmes.
- Support audit delivery teams with the development of complex/insightful data analytics tests.
- Adhering to data transfer and security requirements
Accountability: Engagement and Strategy Management
- Executing on delivery of strategic initiatives
- Support audit delivery teams with the identification and delivery of analytics solutions
- Provide training to audit staff on how to develop and execute basic analytics programs
Accountability: Stakeholder Management
- Build relationships with data warehouse stakeholders and data providers.
- Share knowledge with Internal Audit colleagues and peers in the business. Be open to learn from others through feedback given to you.
- Treat all colleagues fairly, regardless of background or circumstance.
- Be comfortable to challenge others; be prepared to be challenged.
- Update the Data Analytics Champions and Data Analytics Leads with progress of development.
- Build relationships with key clients including data warehouse stakeholders and business MI teams.
- Build strong relationships and mutual trust with all internal stakeholders (i.e. audit teams)
- Understand the needs of client/customer and make decisions using this knowledge.
Accountability: Knowledge Management
- Own and drive personal learning to support achievement of career aspirations.
- Improve technical knowledge through self-learning or training including mandatory CPE requirements.
- Knowledge sharing with Internal Audit colleagues and peers in the business.
- Develop/implement data analytics driven business-monitoring programmes to support the Internal Audit teams.
- Research & Development of data analytics tools and trends to bolster the team’s knowledge
- Where applicable, attend conferences and training to grow the awareness and knowledge base around Analytics and/or Internal Audit.
Accountability: Decision-making and Problem Solving
- Develop analytics for all areas of the audit process (risk assessment, controls testing and outcomes testing), as well as using analytics as a tool to support processes and procedures throughout the process
- Update the Data Analytics Director and audit team with progress and observations
- Proactively take on additional tasks as requested by Vice Presidents / Directors / Managing Directors
- Suggest practical ways of improving audit work through the use of analytics
Education and Experience Required
- B Degree (Commercial, Informatics, Statistics, Computer Science)
- Higher Diploma/Certification in Data Analysis or Software Development
- Programming / software development experience
- Knowledge of data Visualisation/Dashboards tools (To name a few: Qlik, Tableau, PowerBI, R ggplot, R Shiny)
- 5 years technical experience
- Relevant professional qualifications or certifications (To name a few: Statistics, Data Analysis, Data Mining, SAS Certification, DBMS, SQL, PERL, TERADATA, Data warehouse, R, Python, Machine Learning)
- Experience with advanced analytics (To name a few: Predictive and prescriptive analytics using neural networks and decision trees, development and/or execution of software robots)
- Knowledge about new and emerging data analytics technologies)
- Practical financial services industry knowledge
- Experience in risk based auditing or risk/control activities