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Front Office Market Risk Quant - VP

  • Job type: Permanent
  • Location: New York
  • Salary: Competitive
  • Job reference: 336821/002_1563229702
  • Sector: Selby Jennings, Risk Management
  • Date posted: 15/07/2019

A top multinational investment bank is growing its all-star risk modeling team that is responsible for best-in-class market risk (VaR) and market risk capital modeling (IRC, CRM). This high performing team is led by a well-known former front office quant. On a day to day, the team designs, develops, and implements market risk models across asset classes (FI, IR, FX, Equities, Commodities) using Python/C++. This is a highly esteemed group with functionality spanning equal parts quantitative and technical. This dynamic team is uniquely positioned in the market due to its cross-asset coverage and daily front office exposure given the nature of the work. The team and firm employ some of the leading technology and data platforms in the industry with emphasis on further developing additional machine learning capabilities.

The team is ideally looking for someone who has a quantitative and analytical background with comfortability in programming across Python and/or C++, and a very high level understanding of regulations including FRTB. Most of the group are comprised of exceptionally bright PhDs (a plus, not a requirement) and former front office quants. The group is not siloed like traditional market risk teams and everyone is equally responsible for both development and implementation, and develops their models from scratch.

THE ROLE

  • Design, develop, and implement internal risk and regulatory models such as VaR, IRC, CRM, and Regulatory CVA across a variety of asset classes

  • Leading FRTB model development

  • Conduct theoretical modeling, empirical-testing, statistical analysis of market data, historical back-testing, numerical implementations, and work on model methodology

  • Provide analytical support to risk managers and resolve modeling related issues and inquiries with front office

BACKGROUND

  • Graduate degree in quantitative subject matter (Math, Physics, Statistics, Econ, Engineering, etc.), post-doctorate degree a plus but not required

  • 8+ years experience in risk analytics, model development, front office, or risk methodology

  • Programming proficiency in Python or C++

  • A strong grasp financial products in one or more of the following: Interest rates (including exotics), Corporate Bonds and Credit Derivatives (CDOs, CLOs, etc.), Equities, FX, and/or Commodities

  • Analytical experience in financial mathematics, time series, statistical analysis, numerical analysis, etc.

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