Quantitative Analyst – Market & Counterparty Risk

Quantitative Analyst – Market And Counterparty Risk Modelling

Our client an Investment Bank is looking for AVP / VP level Counterparty and Market Risk Quantitative Analysts.

Key Responsibilities of role Working in close partnership with other risk teams and stakeholders (systems, reporting, regulatory, Front Office), the successful candidate will contribute to SIGMA’s mission, taking responsibilities for the following:

• Lead methodology projects, gathering and documenting requirements, considering stakeholder interests, regulatory constraints and any potential deficiencies in the current methods exposed by quality assurance processes;
• Investigate, analyse and design risk methods, respecting the aims of accurately capturing risks whilst considering system or other constraints;
• Design, develop and test code changes required to implement the risk methods in the risk systems, whilst assisting the technical teams responsible for optimisation and promotion of the code to the production environment;
• Contribute to the quality assurance processes surrounding risk measurement including back-testing and the VaR Adequacy (P&L Explain) process;
• cooperate with the risk model validation teams in the review and approval of risk models;
• Support regulatory interactions, participating in industry working groups and Quantitative Impact Studies (QIS);
• In a transactional or advisory capacity, assist risk managers and Front Office in the prompt, accurate and astute risk assessment of deals, where the standard and systematic methods may not be applicable or appropriate.

Experience, Qualifications & Competencies

To be successful in this role, the candidate must meet the following requirements:

• A strong interest and knowledge of risk management best practises, financial markets and economic developments;
• A strong academic background, with at minimum a Masters in mathematics, physics or quantitative finance or equivalent relevant experience;
• Proven experience in a quantitative risk modelling capacity;
• A practical knowledge of derivatives, their risk drivers and the models used to price them;
• sound understanding of stochastic processes and their application to risk factor simulations;
• Exposure to backtesting methodologies, collateral modelling approaches and initial margin models. Design and implementation of quantitative models, using C# or C++ in a source-controlled environment;
• Strong communication skills, both written and verbal

Please note our advertisements use PQE/salary levels purely as a guide. However we are happy to consider applications from all candidates who are able to demonstrate the skills necessary to fulfil the role.

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