Analytics Manager

2 weeks ago

Kempton Park, South Africa The Foschini Group Full time

**Job ID**:13827**Position Type**:Full-Time**Job Function**:Financial Services / Analytics**Workplace Type**:Head Office**Division**:TFG Financial Services**Province**:Gauteng**Location**:Johannesburg East**Suburb**:Isando (Kempton Park)Position Description:
An interesting and challenging opportunity has arisen within the Analytics Department of TFG Financial Services for a dynamic, highly motivated individual to provide analytical solutions that will improve decision making throughout the credit life cycle.

**Job description**:

- Retrieve and analyse quantitative data using (SAS, SQL, Excel, etc.)
- Development, implementation, and monitoring of all the ECL provisioning models
- Development and maintenance of Financial Mathematical models (probabilistic and forecasting)
- Portfolio monthly reporting/tracking
- Liaising and work with stakeholders to identify business needs, project scopes and deliver on agreed projects outcomes
- Development and deployment of predictive models and analytical strategies to improve decision making throughout the credit life cycle of the TFG account base
- Investigate appropriate statistical methodology and data mining/analytical techniques applied to modelling process to deliver and deploy robust and effective models
- Identify risks, measuring thereof, and forming strategies to contain or mitigate risks
- Effective communication and presentation of analytical results to different stakeholders
- Conducting peer-on-peer quality assurance to ensure consistency in delivery
- Documentation of analytical processes and results, adhering to agreed documentation standards
- Training/upskilling Junior staff in the team

**The ideal fir for the role**:

- A degree in a numerical discipline, preferably Mathematics/Statistics/Operations Research
- Good understanding of IAS 39/IFRS 9 framework
- 5 years’ experience in credit risk modelling i.e., PD, EAD, LGD, etc.
- Good data interpretation skills
- Knowledge of statistical software packages (SAS/SPSS) - SAS Enterprise Miner would advantageous
- Understanding of the credit industry and credit life cycle management
- Customer centric approach
- Energetic, able to think innovatively, driven to succeed, self-disciplined and team player
- Ability to influence and build relationships with various stakeholders across levels and functions and can work collaboratively

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