Profile:

Looking for candidates with experience in derivatives pricing models. The candidate can be working in model validation, model risk, model development, Quantitative Research (QR), or strats. Experience in any asset class is fine; Rates derivatives experience is a plus but not mandatory.

Keywords to look for in resumes:

Stochastic calculus, Probability, Option pricing, Monte Carlo, Derivatives and derivatives pricing model names such as Black-Scholes, Heston, SABR, Hull-White, etc.

As a Quant Model Risk Vice President, you will assess and help mitigate the model risk of complex models used for valuation and risk measurement of derivatives, with a focus on Interest Rates derivatives. You will work closely with model developers, Front Office, Valuation Control Groups, and model users, while gaining exposure to a variety of business and functional areas.

Job Responsibilities:

- Carry out model reviews by analyzing the conceptual soundness of complex pricing models, engines, and reserve methodologies.

- Assess model behavior and the suitability of pricing models and engines for specific products/structures.

- Provide guidance on model usage and act as the first point of contact for the business on new models and changes to existing models.

- Develop and implement alternative model benchmarks, compare outcomes across models, and design model performance metrics.

- Evaluate model performance on a regular basis.

- Liaise with model developers, Front Office, Risk and Valuation Control Groups to provide guidance on model risk.

- Manage, develop, train, and mentor junior members of the team.

Required Qualifications, Capabilities, and Skills:

- 7+ years of experience in a quantitative finance environment (e.g., Front Office quantitative research, model validation, strats, hedge funds), with exposure to derivatives pricing.

- Strong conceptual and mathematical knowledge of derivatives pricing, simulation techniques, probability theory, stochastic processes, partial differential equations, statistics and numerical analysis.

- Practical knowledge of derivatives, their risk drivers, and quantitative models used for pricing and hedging derivatives.

- Exposure to at least one of the following asset classes: interest rates, FX, equity, credit, or commodities, preferably from a model validation or FO perspective.

- MSc, PhD, or equivalent qualification in a quantitative discipline such as Mathematics, Quantitative Finance, Statistics, Engineering, Physics, or a related field.

- Inquisitive mindset, with the ability to ask the right questions, challenge assumptions, and escalate issues appropriately.

- Excellent written and verbal communication skills.

- Strong coding skills, for example in C/C++ or Python.

Preferred Qualifications, Capabilities, and Skills:

- Direct experience with interest rate derivatives and related pricing models such as SABR and Hull-White.

- Familiarity with model risk management frameworks, model governance, benchmarking, and independent model validation.