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We Offer 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.
The Exposure Analytics team is responsible globally for methodology, in-house development and production implementation of the Monte Carlo exposure models used by Credit Suisse to determine capital requirements for CVA and Default risk and to compute internal risk measures of Counterparty Credit Risk on derivatives positions.
The models developed in the team are the core components at the heart of the multi-year "Strategic-EPE" program of the Bank, which is aimed at re-defining exposure methodology and infrastructure across all regions.
We offer a challenging modelling role that includes:
Modelling the joint evolution of the stochastic risk factors underlying derivative trades across asset classes (e.g. equity, credit, FX, interest rates, commodities).
Pricing models for financial derivatives.
Prototyping, backtesting and benchmarking of model candidates.
Development of production implementation of models within the C++ library owned by the team, which forms part of the Front-to-Back analytics infrastructure of CS.
Addressing requests from model validation, internal/external auditors and various regulators (e.g. in the context of Basel framework) including analysis of the assumptions and limitations of the models.
Interaction with internal business partners such as Front Office, Credit Officers, Pre-trade Analysis, IT.
Open to discussing flexible/agile working.
She/he will offer M.Sc. or Ph.D. in Financial Mathematics, Quantitative Finance or equivalent working experience.
You will demonstrate work experience in derivatives pricing or risk modeling.
You will have a solid understanding of financial markets and derivative products.
Programming experience, particularly in C++. Other programming experience also desirable (e.g. Python, C#, Matlab, VBA, F#, Mathematica).
Suitability to work well within a team, engendering good team ethics.
Ability to write rigorous and clear model documentation.
Fluency in English as well as good communication skills.