Job Description

Company Description

Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities - plus the chance to work alongside some of the sector's most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We're passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.



Responsible for dynamic fraud rules algorithms, quality assurance and governance underpinning new analytics development.

Provide 24/7 fraud rule monitoring support to effectively prevent and detect flash fraud.

Drive innovation in fraud risk prediction, prevention, detection models using predictive analytics and machine learning models.

• Maximise business value creation and deliver exceptional customer experience whilst minimising external fraud risk and related losses through robust configuration of fraud rules, algorithms, decision trees. This includes enabling Predictive Fraud Modelling, Machine Learning and Analytics capability, group-wide.
• Execution and oversight of all the 24/7 Fraud Rules, Predictive Fraud Modelling and Analytics capability group-wide, and overarching key performance indicators.
• Execution and alignment of the Fraud Rules Governance, Modelling and Analytics Portfolio within the rules management function to achieve the group objectives of becoming a universal bank focusing on customer centricity and economic profit (optimise risk/reward trade-off).
• Develop and manage a balance of real time and batch fraud rules and predictive models to minimise the impact of financial crime to the bank, its customers and shareholders.
• Responsible for Data Sourcing, Mining and Staging using ETL, SQL, SSIS and SAS development
• Data Wrangling and Feature Engineering for Model Data Management, Development and Life Cycle management using R, Python, C#, SAS and SQL programming
• Expert handling and management of structured and unstructured data
• Setting up of data pipelines, event hubs and ingestion using Big data Platforms and Cloud technology such as MS Azure, Cortana Intelligence Suite and SAS Analytic Suite
• Driving Action With Big Data Analytics and Machine Learning technology
• Visual representation of fraud patterns, statistics and BI (SAS, QlikView, MS Excel and Power BI)
• Inculcating and supporting a Strategic Analytics Culture
• Responsible for Systems and Model management and underpinning Data Analytics and Fraud rules management support.
• Manage the fraud model performance , QA , validation and ROI on the relevant fraud management platforms
• Hands-on in analysing and understanding large amounts of historical data to determine the most suitable fraud modelling techniques and leading model development and enhancement efforts.
• Bringing expertise with different types of algorithms and modelling processes
• Machine Learning and AI
• Meeting roadmap deliveries at high quality and on time.
• Working directly with internal and external business partners and supporting models in production
• Prepare appropriate Fraud Rules Governance performance reports and provide support to FRS Heads in unpacking fraud rule performance
• Provide data-driven fraud insights into FRG sessions to inform FRS Heads and business stakeholders to make the appropriate decisions

• Honours Degree in Mathmatics
• Cortana Intelligence Suite, SQL, Python, and SAS Analytics Suite
• Reputable Data Scientist Degree, Data Mining/Machine Learning/Statistics Expertise (preferred)

• 6 Years Advanced data analytics
• Advanced experience in Financial Services, Predictive Modelling and Analytics capability development and management with a well-developed risk management knowledge of the personal and business banking, and wealth environments and related fraud through practice.
• Proven Predictive Fraud Modelling and Analytics

Standard Bank