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JPMorganChase

Quant Model Risk Associate

Posted Yesterday
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Hybrid
London, Greater London, England
Mid level
Hybrid
London, Greater London, England
Mid level
The Quant Model Risk Associate assesses risks of complex models, performs model reviews, and collaborates with developers on model risk management.
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Job Description
We are looking for a new member to join our Commodities team in the Model Risk Governance and Review Group which is responsible for end-to-end model risk management across the firm.
As a Quant Model Risk Associate within our Risk Management team, you will be responsible for assessing and mitigating the risks associated with complex models used for valuation, risk measurement, capital calculation, and decision-making purposes. This role also provides the opportunity to gain exposure to various business and functional areas, as well as collaborate closely with model developers and users.
Job responsibilities

  • Carries out model reviews: analyze conceptual soundness of complex pricing models, engines, and reserve methodologies; assess model behavior and suitability of pricing models/engines to particular products/structures
  • Provides guidance on model usage and act as first point of contact for the business on all new models and changes to existing models
  • Develop and implement alternative model benchmarks and compare the outcome of various models; Design model performance metrics
  • Liaises with model developers, Risk and Valuation Control Groups and provide guidance on model risk
  • Evaluates model performance on a regular basis


Required qualifications, capabilities, and skills

  • Excellence in probability theory, stochastic processes, statistics, partial differential equations, and numerical analysis
  • MSc, PhD or equivalent in a quantitative discipline
  • Inquisitive nature, ability to ask right questions and escalate issues
  • Excellent communication skills (written and verbal)
  • Good understanding of option pricing theory (i.e. quantitative models for pricing and hedging derivatives)
  • Good coding skills, for example in C/C++ or Python


Preferred qualifications, capabilities, and skills

  • Experience with commodity derivatives
  • Experience in a FO or model risk quantitative role.


About Us
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Risk Management helps the firm understand, manage and anticipate risks in a constantly changing environment. The work covers areas such as evaluating country-specific risk, understanding regulatory changes and determining credit worthiness. Risk Management provides independent oversight and maintains an effective control environment.

Top Skills

C/C++
Python

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