Model Development Lead # 104317

The Risk Division is a highly visible, dynamic area of the firm where you can be an integral part of the decision making that supports the bank’s business. Our responsibilities range from Enterprise Risk management to risk and finance reporting, and regional risk teams covering the risk management for our entities. The Risk division's long-term success depends on our ability to achieve our vision and fulfill our mandate. Ultimately, this depends on the skills, experience and engagement of our employees. We offer a collaborative and entrepreneurial environment that offers direct contact with senior management and encourages leadership at all levels.

An opportunity to work for the team responsible for developing and maintaining the Monte Carlo models used by Credit Suisse for the calculation of CVA and Default risk capital, as well as for the monitoring of counterparty exposure against the bank’s limits.

The opportunity to play a key role in the Strategic-EPE programme of Credit Suisse, aimed at re-defining the exposure methodology of the bank and implementing it on the new Front-to-Back infrastructure.

A challenging role that includes:

  • Developing, implementing and maintaining two important models in the counterparty credit risk exposure framework that include dynamic modelling of initial margin and the exposure calculation of cleared derivatives
  • Development of production implementation of models within Credit Suisse integrated Front-to-Back infrastructure
  • Interaction with internal business partners such as Front Office, Credit Officers, Pre-trade Analysis & IT
  • Addressing requests from regulators and support the model submission work

Open to discussing flexible/agile working.

  • University degree in Physics, Engineering, Quantitative Finance or similar or equivalent work experience
  • Solid experience in a quantitative role/s in Finance, e.g. derivatives pricing or risk modelling
  • Knowledge and experience with Counterparty Credit Risk
  • Programming experience, particularly in C++ and ideally with exposure to quant libraries. Other programming knowledge also desirable (e.g. R, Python, VBA, Matlab, C#)
  • Understanding of financial products
  • Strong analytical and problem solving skills
  • Willingness to learn, ability to pick up concept quickly
  • Highly committed and strong team player competences