Senior Quantitative Analyst

  • Competitive
  • New York, NY, USA
  • Full time, Permanent
  • BNP Paribas
  • 15 Nov 17

Business Overview: The Intermediate Holding Company (“IHC”) program structured at the U.S. level across poles of activities of BNP Paribas provides guidance, supports the analysis, impact assessment and drives adjustments of the U.S. platform’s operating model due to the drastic changes introduced by the Enhanced Prudential Standards (“EPS”) for Foreign Banking Organizations (“FBOs”) finalized by the Federal Reserve in February 2014, implementing Section 165 of U.S. Dodd-Frank Act.

Department Overview:
SIGMA is the quantitative modelling team with overall responsibility for market, liquidity and counterparty credit risk methods within BNP Paribas. The team is primarily based in London, with a presence in Paris and Brussels and has recently expanded into the US.

SIGMA sits within Enterprise Risk Architecture (ERA), which is part of the Risk Function of the group. The Risk Function is globally accountable for the definition of official risk policies, guidelines and procedures, as well as the quantification and monitoring of risks taken by the various business lines, to ensure alignment with risk appetite and policies. At BNP Paribas, our well-developed risk management culture is based on a long-term vision, a committed management, and a strong and independent organization.

Within ERA, SIGMA’s mission is to develop and continually improve the group’s risk modelling & measurement, analysis and back-testing capabilities. SIGMA is organized in four streams, each responsible for a given asset class (IRFX, Credit / Repo, Equity / Commodity) or transversal aspects of risk methods (Cross-Product), supported by two architects responsible for ensuring consistency across methodological research and development activities.

The team’s remit includes all Internal 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.

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, analyze and design risk methods, 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 optimization 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.

Whilst the role may involve all aspects of the team-wide responsibilities, the candidate will represent the department locally in the US, liaising with the Federal Reserve on methodological matters and acting as a subject matter expert on methodological topics locally.

To be successful in this role, the candidate should meet the following requirements:
• 7 – 10 years of relevant industry experience, preferably at a large IB.
• A strong academic background, with at minima a Masters in Mathematics, Physics or Quantitative Finance.
• A strong interest and familiarity with risk management best practices, financial markets and economic developments;
• Proven experience in a quantitative finance environment, in a market risk modelling capacity; other backgrounds (e.g. Front Office quantitative research, model validation, counterparty risk) may be considered
• 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;
• 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 and to frequent contacts with the Federal Reserve, in the context of the market risk internal model validation and on-going model improvements.
• A good understanding and awareness of the regulatory framework for banks operating in the US is highly desirable; further knowledge of BIS regulations (Basel 3, FRTB), as well as, previous experience in interacting with supervisors (e.g. in a model validation capacity) would also constitute a distinct advantage.

In addition, the candidate 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.

Preferred qualifications:
• A Ph.D. is preferred but not essential, depending upon level of experience;
• 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.
• 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 is a plus;

FINRA Registrations Required: 
• Not Applicable