JOB DESCRIPTION
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.