Quantitative Risk Analyst Graduate

Our quantitative risk work is usually required towards the end of project study phases which means that we have tight deadlines. A typical project ranges from 1 week for small projects and 4 weeks for large projects. We spend quite a lot of time collecting data from clients, which is then followed by the modelling process. Once the models are developed initial results are produced which are then discussed with the client. We often do re-runs of the models with changes received from the client. Once the client is satisfied with the results, a final report is developed.

The work does sometimes require analysts to work after hours to meet deadlines, but this is infrequent, and we try to manage client expectations to avoid unnecessary late nights.

We work from our offices in Centurion, but most of our analysts work from home for 2 or 3 days a week. We would therefore expect you to have a reliable internet connection and an environment that is suitable for attending and facilitating meetings. We have solar power at our offices and would expect you to attend or facilitate meetings from the office if you suspect your power at home may let you down.

What are we looking for?

We have an opportunity for a Quantitative Risk Analyst to join our team as part of our graduate development programme. We would require this person to have the following skills and qualifications:

• A BSc degree in Quantitative Risk Management, preferably at honours level, or a similar degree which covers statistics and financial mathematics.
• A thorough understanding of financial modelling.
• A thorough understanding of statistical methods, probability distributions, Monte Carlo simulations, and Markov processes.
• A good command of Microsoft Excel.
• Very good verbal and written communication skills.
• Excellent ability to work with clients to collect data and to explain model outcomes in simple terms.
• We do not require experience in actual project risk modelling, but it would be an advantage if you have experience in this area.

The following are not mandatory but will be advantageous:

• Knowledge of R and/or Python.
• Programming experience in VBA or C#.