Head of Data Engineering and Analytics: Fraud Risk Operations

Empowering Africa’s tomorrow, together…one story at a time.

Job Summary

Define and execute the Data Science strategy supporting Fraud Risk and Fraud Operations, ensuring alignment to business objectives, risk appetite, regulatory requirements, and customer outcomes.

Lead the design and evolution of the fraud data architecture, establishing scalable, secure, and resilient data platforms that enable advanced analytics, real-time decisioning, and operational intelligence.

Own and oversee all data engineering capabilities required to support machine learning models, management information (MI), real-time monitoring and detection engines, customer relationship management (CRM) platforms, and broader fraud technology solutions.

Lead the development, deployment, and continuous optimisation of machine learning and analytical models, ensuring measurable improvements in fraud detection, prevention, operational efficiency, and customer experience.

Own model risk management, data governance, and regulatory compliance across the function, ensuring robust controls, validation frameworks, audit readiness, and adherence to internal and external standards.

Enable and govern enterprise fraud reporting and insights, including data creation, automation, visualisation, and performance monitoring to support strategic, operational, and regulatory decision-making.

Drive innovation through Artificial Intelligence, sponsoring, enabling, and overseeing all AI proof-of-value and proof-of-concept initiatives, and converting successful use cases into scalable business capabilities.

Provide leadership across Data Science, Data Engineering, Analytics, and AI teams, building organisational capability, fostering innovation, and ensuring delivery of the fraud management strategy.

Job Description

Data Science & Engineering
• Work with business & technology (e.g. CSO, CTO, CIO, Infrastructure, SE) stakeholders to define the data requirements for the business
• Translate the business requirements into a Data Strategy (integrating data science & engineering requirements) for optimal results
• Leverage the Group Data rails to translate the business requirements into a sound data architecture & direction for proactive Technology Services monitoring / management
• Lead the data automation agenda for Technology Services Monitoring & Management (where it makes sense to do so)
• Assume one stop shop accountability for all services monitoring / management related data products and services
• Guide the business on the appropriate data solutions & range of strategic data choices to be made
• Apply & cascade design thinking practices across the team to deliver architecturally & technically sound data solution designs & blueprints
• Ensure & Oversee that solution designs & blueprints are translated into leading practice data engineering solutions (& related e.g. source code) that effectively deploy & optimize data retrieval, storage and distribution
• Leverage deep data science & engineering expertise to oversee the mining and modelling of raw data sets with leading practice data science toolsets ee.g. advanced statistics, data wrangling, data mining, data analysis, feature engineering & predictive modeling, story-telling, distributed computing & data visualization, machine learning, data intuition
• Lead the detailed scoping, prioritisation & integration planning for data solutions
• Lead the data automation agenda across the estate
• Leverage deep technical expertise to guide and coach data science & engineering teams on appropriate solutioning
• Ensure data products and services translate for business into relevant, quality assured, accurate and commercially impactful data sets that enable strategic & operational decision making for the short, medium & long term
• Meaningfully contribute & ensure solutions align to the design & direction of the Group Architecture & Infrastructure standards, principles, preferences & practices. Short term deployment must align to strategic long term delivery.
• Strategically & operationally monitor the performance of data products and solutions – ensuring cost to value for our businesses (ROI of the data provided)
• Promote data literacy across the enterprise by sharing best practices and showing tangible business impact & recommendations as a direct result of the the data solutions provided
• Proactively stay ahead of the curve on data science & data optimization trends, tools, techniques as well as data engineering trends & leading practice tools and programs (e.g. automation, virtualization, AI, Machine Learning, Programming languages, Open Source Software e.g. Hadoop) & transition the organisation to advanced methods for the continuous optimization of data

Delivery Management (where there is a specific product / service you manage)
• With fluency in the deployment of agile methodologies, resource & manage the appropriate number and nature (skill & capability) of squad based teams to execute on both Run & Change elements of data delivery
• Ensure agile practices are implemented and sustained for effective delivery to business e.g. RETRO’s etc.
• Positively & proactively manage senior stakeholder relationships & expectations
• Proactively engage with & partner CTO, CSO, SE, Risk and broader enablement functions to drive alignment & leading practice in data solution design & deployment

People
• Proactively attract, recruit, develop, retain, reward & deploy a diverse resource base aligned to an ever evolving environment (ahead of demand)
• Build a high performance team environment through self-directed teams & PM alignment with agile working practices (including daily, weekly, etc. sprint routines, regular & honest feedback etc.)
• Accountable for the right people in the right teams to deliver on our tech strategy (always!)

Financial & Vendor Management, Risk & Governance
• Carry the ‘one stop shop’ accountability for all data compliance, governance & overall risk associated with data solutions
• Manage & Apply the organization & regulatory risk & governance frameworks
• Manage all vendor selection processes (for data specifically and where relevant) & take full accountability for all related commercial impact
• Deliver on time & on budget (always)
• Hold one stop shop accountability for data quality & data integrity (always) across the business area
• Provide risk, governance, compliance & broader regulatory reporting as required
• Contribute to risk, governance, compliance & broader regulatory processes as a data expert (if & when required)
• Deliver on time & on budget (always)

Education

Bachelor's Degree: Information Technology

Absa Bank Limited is an equal opportunity, affirmative action employer. In compliance with the Employment Equity Act 55 of 1998, preference will be given to suitable candidates from designated groups whose appointments will contribute towards achievement of equitable demographic representation of our workforce profile and add to the diversity of the Bank.

Absa Bank Limited reserves the right not to make an appointment to the post as advertised