Internal Audit: Data Management Specialist at Absa Group Limited (Absa)

Job Summary

• Absa Internal Audit (IA) is looking for a dynamic, innovative and motivated individual to enable and support IA with continuous analysis, data mining and insight generation for IA reporting and planning purposes.  The successful individual should have IA experience, and knowledge of IA controls and organisational risk management practices, within the Financial Services industry.  The individual will need to leverage deep data science expertise in data mining, data analysis, feature engineering, predictive modeling, storytelling, data visualisation, machine learning tools and data intuition to define, build, operationalise and continuously improve data solutions that deliver relevant, quality assured, accurate and commercially impactful data for IA reporting and planning purposes.

Job Description

Key accountabilities

• Advanced Internal Audit (IA) experience, and focused understanding of internal controls and organisational risk management practices to support complete, accurate and valid IA reporting and planning.
• Continuous analysis of IA data, and development of relevant insights (including trends and predictive analysis) for IA reporting and planning.
• Advanced understanding of IA root cause and issue management analysis to provide timely and relevant information for reporting and planning.
• Continuously seeking new and improved ways for data extraction and consumption by relevant IA stakeholders for reporting and planning.
• Advanced understanding of available data analysis and machine learning tools to support robust and forward-thinking insight generation for reporting and planning.
• Adopting of agile work practices and working closely with senior members of the IA team to collate, consolidate and visually present data-led insights for reporting and planning.
• Participate in design thinking processes to determine and confirm priority IA questions/ data challenges to be solved for, by translating these into data requirements and defined data-led solutions for reporting and planning. 
• Design fit for purpose data interpretation and analysis approaches, and create customised data models, algorithms, machine learning tools and recommendation engines to achieve the desired IA outcomes for reporting and planning, 
• Use advanced data science skills to mine and interpret IA data.  These include but are not limited to: advanced statistics, data wrangling, data mining, data analysis, feature engineering and predictive modeling, distributed computing, machine learning tools and data intuition, to analyse and interpret complex IA data-sets for reporting and planning.
• Ability to apply quality assurance frameworks to test model and analysis techniques (e.g. algorithms, models) to support the quality and integrity of IA data used for reporting and planning. 
• Produce business insights and recommendations based on data analysis and modeling concluded, and where relevant with knowledge and experience of e.g. Java, Scala, Python, Hadoop, Apache Spark, Kafka or similar.
• Use storytelling and data visualisation techniques to maximize impact and deliver a user-friendly product for reporting and planning. 
• Contribute to the consolidation of data solutions into viable end products (in IA business-language) that can be leveraged on an ongoing basis e.g. dashboards, reports etc.
• Present data analysis (trends, insights, forecasts) and findings to IA, to show tangible business impact to be derived from the data science process. 
• Where applicable, to facilitate peer reviews and feedback on new data solutions for reporting and planning.
• Where applicable, contribute to the assessments of the effectiveness and accuracy of new data sources and data gathering techniques.
• As far as possible, to promote data literacy within IA by sharing best practices and showing tangible business impact and recommendations as a direct result of the data solutions provided.
• Stay ahead of the curve on data science trends and leading practice data science tools and techniques, and be able to transition IA to advanced methods for the continuous optimisation of a data-led environment. 
• Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise-wide Risk Management Framework and Absa Policies and Policy Standards.
• Understand and manage risks and risk events (incidents) relevant to this role.

Experience/ Requirements:

• Internal Audit (IA) background/ experience (Preference - Internal Auditor).
• Advanced knowledge of IA controls, language and organisational risk management practices.
• Experience in the Financial Services industry.
• Data Analysis and statistical reporting.
• Experience managing people (small to medium size teams).
• Results and output-orientated.
• Ability to learn quickly.
• Have a logical approach to problem solving.
• Able to work closely and build excellent relationships with key stakeholders.
• Able to manage, develop and mentor less experienced members of the team.
• Effective communication skills.

Potential Qualifications:

Relevant Business-related Degree or Tertiary Technical Degree, in:

• Actuarial Sciences, or
• Data Analytics and Data Sciences, or
• Internal Auditing, or
• Chartered Accountant (CA(SA)), or
• Masters in Business Administration (MBA).

Years of Experience:

• Minimum of 5 years-experience