Quant Model Risk Associate

2 weeks ago

London, Greater London, United Kingdom JPMorgan Chase Full time £60,000 - £80,000 per year

Do you want to join the team which makes a difference in a bank? Financial institutions routinely use models for a broad range of activities including credit underwriting, valuing financial instruments, measuring and managing risk, assessing the adequacy of reserves and capital resources, and many other applications. Model Risk arises from the potential adverse consequences of making decisions based on incorrect or misused model outputs and reports, leading to financial loss, poor business decision-making, or reputational damage.

As a Quant Model Risk Associate - Market Risk working in Model Risk Governance and Review Market Risk, you will play a crucial role in reviewing  market risk models (such as Value-at-Risk, specific risk, risk factor simulation) used in connection with regulatory capital measurement, and contribute to a range of model risk governance activities.

The Model Risk Governance and Review (MRGR) group is responsible for conducting model validation to help identify, measure, and mitigate Model Risk. The objective is to ensure that models are used appropriately in the business context and that model users are aware of the models' strengths and limitations and how these can impact their decisions. Within MRGR, the MRGR Market Risk (MRGR MR) team performs reviews of the Firm's Market Risk models to ensure that the way in which JP Morgan quantifies, monitors, and manages risk is robust.  This role involves examining the behavior of these risk models by assessing their performance for different exposures and in varying market conditions. It entails exposure to a broad range of models, including the pricing models used to value derivatives, and statistical models of the risk factors used to estimate possible market scenarios.  

Job responsibilities

  • Evaluate conceptual soundness of model specification; reasonableness of assumptions and reliability of inputs; completeness of testing performed to support the correctness of the implementation; robustness of numerical aspects; suitability and comprehensiveness of performance metrics and risk measures associated with use of a model.
  • Design and implement experiments to measure the potential impact of model limitations, parameter estimation error or deviations from model assumptions; compare model outputs with empirical evidence and/or outputs from model benchmarks.
  • Evaluate model performance on an ongoing basis and in periodic re-reviews 
  • Identify market conditions under which a model's performance may degrade. 
  • Liaise with model developers,  Finance and Risk professionals to provide guidance on model risk and usage. 
  • Document and explain review findings to model developers and risk management. 

Required qualifications, capabilities, and skills

  • An advanced degree (for example, MSc or PhD) in a subject such as Applied Mathematics, Economics, Physics, Statistics, Engineering or similar.
  • Deep understanding of probability theory, financial mathematics, time-series analysis, statistics, and numerical methods.
  • Experienced in one or more programming languages (e.g., Python) and in working with complex data sets.   
  • Excellent analytical and problem solving abilities.
  • Inquisitive nature, ability to ask right questions and to escalate issues; a risk & control mindset.
  • Excellent communication skills (written and verbal).
  • Teamwork-oriented mindset.

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