Senior Quantitative Analyst

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 Bank’s 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. Mission SIGMA’s mission is to develop and continually improve the group’s risk modelling & measurement, analysis and backtesting capabilities. Job Summary & 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 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. 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. 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 supervisory bodies is a plus. A good understanding and awareness of the regulatory framework for banks is desirable. Experienced Candidates with Academic Research Background Are welcome from the range of disciplines: from the field of financial mathematics to broader fields of mathematics, physics and engineering. We welcome both academic and industrial scientists. Successful candidate will be provided internally with on the job training in financial mathematics and banking fundamentals. Candidates expected to have a PhD with further research experience. Candidates should demonstrate a proven record of research and academic excellence; published work is a plus. More senior candidates are expected to demonstrate leadership in collaborative research projects. 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 joint research with other research teams is a plus. Reasonable coding skills are expected. Additional Abilities In addition, a candidate from any background will have the ability to: Work to meet 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. What We Offer The successful candidate will have the opportunity to further develop his or her quantitative skillset, joining a multicultural team of seasoned quantitative analysts eager to stay abreast of the latest market and industry developments. As such he or she will also have the opportunity to contribute to shaping the Bank’s and the industry’s future of internal models and risk management. SIGMA participates in Risk Model Fundamentals and Research Lab and successful candidates, once integrated into the team, will be given an opportunity and an option to participate in Lab projects. The results from the Lab and SIGMA in general are regularly presented at major international conferences. Members of SIGMA also publish in professional refereed journals. The role is transversal in nature and the successful candidate will contribute to improving BNP Paribas’ internal models in both market and counterparty risk spaces. The role is not limited to quantitative modelling and will also allow the candidate to further develop or strengthen his or her development skillset (our proprietary library is implemented in C#). Training programs, career plans and internal mobility opportunities, national and international thanks to our presence in different countries. Diversity and Inclusion Committee that ensures an inclusive work environment. In recent years, several employee communities have been created to organize diversity and inclusion awareness actions (PRIDE, We Generations and MixCity). Corporate volunteering program (1 Million Hours 2 Help) in which employees can dedicate time out of their working hours to volunteer activities. Hybrid telecommuting model (50%). Diversity and Inclusion Commitment BNP Paribas Group in Spain is an equal opportunity employer and proud to provide equal employment opportunity to all job seekers. We are actively committed to ensuring that no individual is discriminated against on the grounds of age, disability, gender reassignment, marriage or civil partnership status, pregnancy and maternity/paternity, race, religion or belief, sex or sexual orientation. Equity and diversity are at the core of our recruitment policy because we believe that they foster creativity and efficiency, which in turn increase performance and productivity. We strive to reflect the society we live in, while keeping with the image of our clients. #J-18808-Ljbffr