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Model Risk Analytics, VP

  • Job type: Permanent
  • Location: New York
  • Salary: US$140000 - US$180000 per year + Bonus
  • Job reference: 270971/003_1552343438
  • Sector: Selby Jennings, Risk Management
  • Date posted: 11/03/2019

Model Risk Analytics, VP

A premier tier one investment bank is developing a brand new analytics team within Model Risk that will incorporate cutting edge machine learning and deep learning techniques to conduct model analytics and simulations across derivative pricing models of every asset class. The role will include the computation of prices and risk measures for derivative instruments.

The team will solve PDEs and simulate stochastic processes with pricing methods such as monte carlo simulation, numerical integration, and finite differences. Responsibilities also include driving new methodology by conducting research of emerging applications used in pricing and risk modeling.

Requirements

  • Master's Degree or Ph.D. in quantitative field such as Mathematics, Physics, Computational Sciences, Statistics, Engineering, or related fields
  • At least 2+ years of direct work experience in an advanced quantitative finance, model risk management, or risk analytics
  • Programming experience using Python or C/C++
  • Excellent grasp of stochastic calculus and stochastic processes; derivatives valuation a plus
  • Strong mathematical, analytical, and computational skills

Other Desired Qualifications

  • Sound knowledge of stochastic processes (jump, jump-diffusion, diffusion), SDEs, and PDEs
  • Knowledge of one or more of the following approaches: numerical solution of PDEs - finite elements, numerical integration, finite differences, MC simulation of SDE, optimization, machine learning/deep learning
  • Experience or knowledge of Interest Rates, Equity, or FX products with models including jumps, stochastic volatility, or stochastic interest rates
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