Model Risk Analyst — Derivatives Pricing & Governance

Testing Site - JPMC

Greater London

On-site

GBP 60,000 - 90,000

Full time

14 days+

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Job summary

Model Risk Governance and Review Group (MRGR) is seeking a Model Risk Analyst/Associate to review credit derivatives models and enhance governance. You will work with model developers, trading desks, and risk teams to ensure sound pricing models and robust controls across the group.

Ideal candidates bring strong quantitative skills, experience with Monte Carlo methods, and proficiency in C/C++ and Python. The role offers exposure to multiple business areas and demanding analytical challenges in

Qualifications

  • Excellence in probability theory, stochastic processes, statistics, and numerical analysis.
  • Strong understanding of option pricing theory and quantitative models for derivatives.
  • Experience with Monte Carlo and numerical methods.
  • Strong analytical and problem-solving abilities.
  • MSc or equivalent in a relevant field.
  • Proficiency in C/C++ programming and Python.
  • Inquisitive nature with excellent communication skills.
  • Teamwork-oriented mindset.

Responsibilities

  • Analyze the conceptual soundness of complex pricing models and reserve methodologies.
  • Develop and implement alternative model benchmarks and performance metrics.
  • Liaise with model developers, trading desks, and risk professionals to provide guidance on model risk and usage.
  • Maintain model risk control apparatus and serve as the first point of contact for the coverage area.

Job description

Model Risk Governance and Review Group (MRGR) is seeking a Model Risk Analyst/Associate to review credit derivatives models and enhance governance. You will work with model developers, trading desks, and risk teams to ensure sound pricing models and robust controls across the group.

Ideal candidates bring strong quantitative skills, experience with Monte Carlo methods, and proficiency in C/C++ and Python. The role offers exposure to multiple business areas and demanding analytical challenges in

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