Analytics Manager: Credit Risk

**Job ID**:8837

**Position Type**:Full-Time

**Job Function**:Financial Services / Analytics

**Workplace Type**:Head Office

**Division**:TFG Financial Services

**Province**:Western Cape

**Location**:Cape Town North

**Suburb**:Parow (Parow)

Position Description:
With 30 retail brands that trade in fashion, value, jewellery, accessories, sporting apparel, cellular, home ware and furniture, TFG is one of the leading retail groups in South Africa. Besides South Africa, TFG Africa also has a presence in Botswana, Zambia, Namibia, Lesotho and Eswatini through various retail brands. TFG’s vision is: “to create the most remarkable omnichannel experiences for our customers”. TFG has over 4 300 outlets in 26 countries and employs more than 34 800 people with over 26.4 million customers (RSA).

Are you passionate about unlocking the secrets hidden away in data? Do you know (or want to learn even more) about the world of Retail Credit Risk?

TFG Financial Services has an exciting opportunity for a dynamic, highly motivated individual to join our Credit Risk department, managing a team of data scientists and strategic thinkers. If you are someone that enjoys analysing data, formulating strategies and driving change then this position is for you

**The successful individual will be working with the top management in Credit Risk, Credit Marketing & Credit Operations teams in order to**:

- Drive customer acquisition campaigns and strategies, balancing risk with growth
- Help formulate product and marketing strategy
- Implement and optimise existing account management strategies
- Finding opportunities for profit growth across new and existing account base
- Drive credit sales across the TFG product suite
- Portfolio forecasting of account growth, turnover and vouchering
- Optimise marketing strategies through data science, segmentation and models
- Formulate and present proposals to drive growth and minimise risk

**Job description Managing a team of senior data scientists and strategic thinkers, supporting you to**:

- Drive the credit risk marketing strategy for growth through data science and analysis and optimising of past results
- Portfolio forecasting of credit growth levers (active accounts, turnover, risk vintage performance, discount vouchers etc.) on a quarterly basis
- Monitoring portfolio performance against forecast and managing EXCO expectations where needed
- Develop strategies to grow New Accounts within legislative framework and through digital channels
- Existing account management, including limit management, buying position strategies and re-activation campaigns
- Providing analytical solutions to complex business problems
- Support growth across the product suite and across financial services partnerships
- Documentation of analytical processes and results, adhering to agreed documentation standards
- Effective communication and presentation of analytical results and credit-related topics to peers and relevant stakeholders
- Profitability tracking and identification of opportunities derived
- Data mining of credit bureau and other external data to provide insights and trends
- Ensuring appropriate statistical methodology and data mining / analytics techniques are applied to any modelling process to deliver and deploy robust and effective models where necessary
- Model tracking to ensure effective model life cycle management

**To take up this exciting opportunity you should have**:

- A degree in a numerate discipline, preferably Statistics / Mathematics / Operations Research / Engineering (Honours / Master’s degree preferable)
- At least 2 years’ experience managing a small team
- Knowledge and experience in statistical/data management software packages (SAS/SQL) Enterprise Miner would be advantageous
- Knowledge of the credit industry and credit life cycle management is preferred
- Hands-on experience of large-scale customer database data interrogation and manipulation would be advantageous
- Experience with data mining and statistical techniques such as logistic regression, decision trees, cluster analysis etc. is preferred
- Excellent data interpretation skills
- Good strategic and conceptual abilities would be advantageous
- Advanced problem solving, judgment and self-management skills