Credit Optimisation Analyst at TFG (The Foschini Group)

Credit Optimisation Analyst

• An exciting opportunity is available within the Credit Risk Department of TFG Financial Services for a dynamic, highly motivated individual to provide analytical solutions to inform the overall credit strategy. The successful candidate will be part of a team that develops credit scorecards and predictive models. There will also be opportunity to develop portfolio forecasting models, assist with analytical optimisation and perform scenario testing using machine learning techniques. 

Job Description: 

• Assist in the development, implementation and monitoring of credit scorecards
• Develop predictive models to improve the decision-making process throughout the credit life cycle of the TFG account and rewards base, from acquisition to new account decisioning to existing customer management, fraud, collections and recoveries
• Assist in the development of forecasting models using various modelling techniques and machine learning methods
• Support the development of predictive models needed in the optimisation framework and assist with analytical optimisation
• Ensure appropriate statistical methodology and data mining / analytical techniques are used in the modelling process to deliver and deploy robust and effective models
• Extract data accurately and timeously for modelling and optimisation
• Develop variables from external data to improve the accuracy of predictive models
• Derive business insights by leveraging of traditional data sources and alternative data sources
• Support strategy implementation, testing and monitoring
• Compile documentation of analytical processes and results, adhering to agreed documentation standards
• Effectively communicate and present analytical results to different stakeholders 

To take up this challenging position you should have: 

• An Honours degree in Mathematics and/or Statistics
• At least 1 years’ experience in an analytical position
• Excellent data analysis, analytical and problem-solving skills
• Experience in using data analysis software packages (SQL, SAS)
• Experience with data mining and statistical techniques (Logistic Regression, Linear Regression, Decision Trees, etc.)
• Good strategic and conceptual abilities
• Excellent data interpretation skills
• High attention to detail
• Excellent documentation and verbal communication skills 

Preference will be given, but not limited to, candidates from designated groups in terms of the Employment Equity Act.