Quantitative Risk Analyst, Market and Counterparty Risk Modelling - Assista

at  BNP Paribas

THE REQUIREMENTS

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;
• 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 risk measurement and management, including market risk modelling, counterparty credit risk including collateral 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;

In addition, the candidate must have a track record of ability to:

• Work to tight deadlines;
• Work flexibly as part of multiple teams and autonomously;
• Grasp the intricacies of governance-related processes and procedures;
• Juggle changing priorities and a varied workload.

Candidates able to exhibit a curious mindset and those able to demonstrate a strong intuition for identifying and measuring risks of traded instruments will be preferred.

JOB PURPOSE & SCOPE

Purpose:
Carrying out quantitative analyses and developments as laid out in the team’s mission statement
Scope:
Global responsibility for the Group, in line with SIGMA’s team mandate; within SIGMA, the sub-team responsibility comprises a given asset class (e.g. equity/commodity, transversal) or function (e.g. methodology development architecture)

KEY RESPONSIBILITIES

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:

• Contribute to 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, VaR Adequacy (P&L Explain) and model monitoring processes; 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.

Whilst the role may involve all aspects of the team-wide responsibilities, the candidate will specifically contribute to the initiatives within the Cross-Product chapter of SIGMA.

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;
• 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 risk measurement and management, including market risk modelling, counterparty credit risk including collateral 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