Requirements: English
Company: BNP Paribas
Region: Madrid , Community of Madrid
GROUP BNP PARIBAS BNP Paribas is a leading global bank and a prominent international banking institution, operating in numerous locations worldwide and offering multiple financial services, from retail banking to corporate and institutional banking (clients financing, advisory, capital market services). The bank is head-quartered in Paris but has a significant presence in the EU and worldwide. Department Overview Systems InteGrated Methods and Analytics (SIGMA) is a team of specialised risk officers with global accountability for the counterparty, market and liquidity risk methodologies within the Banks RISK function. It also maintains the internal model methodology for operational risk. Organisationally, it is embedded in the RISK Global Framework department and in particular its RISK Models & Regulatory group. SIGMAs mission is to develop and continually improve the groups risk modelling & measurement, analysis and backtesting capabilities . SIGMA is organised in streams, each responsible for a given asset class (IRFX, Credit / Repo, Equity / Commodity) or transversal aspects of risk methods (Cross-Product), as well as a quantitative development / architecture stream. The teams remit includes internal risk models in use within the Bank, such as VaR, Stressed VaR, IRC and CRM models in the market risk space, as well as EEPE, Stressed EEPE, Regulatory CVA models in the counterparty risk space. Job Summary & Responsibilities Working in close partnership with other RISK teams and stakeholders (systems, reporting, regulatory, Front Office), the successful candidate will contribute to SIGMAs mission, taking responsibilities in some of the following areas: Participate in 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 and models, respecting the aims of accurately capturing risks whilst considering system or other environmental 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. Ensure that all methodologies, tools, processes and procedures are documented to a high standard satisfying both internal and regulatory expectations, and that any methodological changes and corresponding decision of governing bodies are promptly reflected in relevant documentation. Contribute to the quality assurance processes surrounding risk measurement including backtesting and 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. Our requirements Candidates with both industry background and academic research background are welcome. To be successful in this role, the candidate should meet the following requirements: A strong academic background, with at minimum a Masters in mathematics, physics or quantitative finance. Both Masters and Ph.Ds. are welcome The Department conducts business in English, thus a good command of both verbal and written English is essential. Further requirements are specified separately for experienced candidates with financial industry background and for experienced candidates with academic research background: Experienced candidates with financial industry background are welcome from banks, investment companies and consultancies: A strong interest and familiarity with risk management best practises, financial markets and economic developments. Experience in a quantitative finance environment, preferably in a market risk or counterparty risk modelling capacity; other backgrounds (e.g. Front Office quantitative research, model validation, hedge funds) are also welcome. Sound understanding of stochastic processes and their application to risk factor simulations. A practical knowledge of derivatives, their risk drivers and the models used to price them; exposure to at least one of the following asset classes: credit, repo, IR/FX, equity, commodities, preferably from a risk management perspective. Design and implementation of quantitative models, preferably using C# or C++ in a source-controlled environment. The role will expose the candidate to a wide range of professionals within the bank. Therefore, communication skills, both written and verbal, play an essential part of the day-to-day role. Previous experience in interacting with Front Office, validation functions and regulatory or supervisor