Data Analyst - Credit Optimisation

The opportunity:

A challenging opportunity is available within the Credit Optimisation department of TFG Financial Services. We are looking for a dynamic, highly motivated individual to develop analytical solutions to business problems using analytical techniques and tools. The successful candidate will be part of a team of data scientists that develops predictive and prescriptive (mathematical optimisation) models to drive credit risk decisioning throughout the business.

Job Description: 

This will involve (but is not limited to):

• Develop predictive models that enable mathematical optimisation to find an optimal solution within the business constraints
• Assist with the development and maintenance of mathematical optimisation solutions to support critical decisioning in credit business
• Ensure appropriate statistical methodology and data mining / analytical techniques are used in the modelling process to deliver and deploy robust and effective models
• Research and implement relevant and new machine learning techniques
• Extract data accurately and timeously for modelling and optimisation
• Develop and maintain Analytics Based Tables (Credit ABTs) to improve the accuracy of predictive models
• Derive business insights by leveraging of traditional data sources and alternative data sources
• Support model and 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 position you should have: 

• 3+ Years’ experience in an analytical/data scientist position focusing on Predictive and Prescriptive analytics is essential
• Honours or preferably Master’s degree in mathematics and/or Statistics including subjects specifically on mathematical optimisation (linear programming / mathematical programming) will be highly advantageous
• Experience in using data analysis software packages (SQL, SAS, R, Python, FICO Analytics Workbench). This includes intermediate to advanced code writing skills in one or more of these languages
• Experience in formulating mathematical optimisation problems (SAS Proc Opt model for example)Experience with data mining and machine learning techniques such as optimisation, logistic regression, linear regression, SVM, decision trees, K-means, cluster analysis etc.
• Previous modelling experience in retail credit will be advantageous.
• Good strategic and conceptual abilities
• Excellent data analysis, analytical and problem-solving skills
• High attention to detail
• Excellent documentation and verbal communication skills 
• Good time management skills

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