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JPMorganChase

Model Risk Governance and Review (MRGR) - London - 2025 ReEntry Program

Posted 2 Days Ago
Be an Early Applicant
Hybrid
London, Greater London, England
Mid level
Hybrid
London, Greater London, England
Mid level
The Model Risk Governance and Review (MRGR) program is designed to support experienced professionals relaunching their careers post-break, focusing on model risk management through independent reviews, governance, and enhancement of estimation frameworks. Responsibilities include overseeing compliance, supporting model development, and managing technology and analytics processes. Candidates will collaborate across teams for effective risk governance in a financial context.
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Job Description
At JPMorganChase, we recognize that rewarding careers do not always follow a conventional path. We value the diversity, fresh perspective and wealth of experience that returning professionals can bring.
The ReEntry program offers experienced professionals, who are currently on an extended career break of at least two years, the support and resources needed to relaunch their careers. The program spans over 30 locations worldwide.
The ReEntry Program is a 15-week fellowship program, beginning April 22, 2025, and ending July 31, 2025 with the prospect of an offer for permanent employment with JPMorganChase at the end of the program. The permanent placements will be based on both business needs and candidate skill set.
Please refer to our ReEntry Overview page for further information regarding the Program.
Group Description
MRGR (Model Risk Governance and Review) is a global team of modelling experts within the firm's Risk Management and Compliance organization. MRGR consists of three groups: Coverage, PPG (Policy, Practice, and Governance), and COO (Chief Operating Office). Each group plays a vital role in conducting and supporting independent model review and governance activities to identify, measure, and mitigate Model Risk within the firm.
Coverage Group
The Coverage group oversees compliance with all MRGR policies and procedures necessary for effective, holistic, and independent model risk management. This includes model review and governance, effective communication with CROs, and LOB stakeholders.
The main requirements for this team are:

  • A Ph.D. or Master's degree in a quantitative field such as Math, Physics, Engineering, Computer Science, Economics or Finance is required.
  • Previous experience in a quantitative or modelling role. Candidates with significantly more experience may be considered for more senior roles.
  • Understanding of Python, R, Matlab, C++, or other programming languages


Policy, Practice, and Governance (PPG) Group
The PPG group supports the Head of MRGR in maintaining and evolving the estimation risk management framework. They own MRGR policy and procedures, quality assurance of MRGR processes, and continuous improvement initiatives. The team is responsible for cross-LOB governance activities, such as the Annual Status Assessment, and owns Estimation Development standards, including those for AI/ML models.
The main requirements for this team are:

  • Undergraduate or Master's degree in economics, finance, computer science or another quantitative discipline
  • Experience in risk management, technology, model development or model risk roles


Chief Operating Office (COO) Group
The COO group supports model risk stakeholders and drives governance activities, focusing on product ownership, process engineering, and software development for model risk technology and analytics. They manage model risk reporting, oversight committees, and regulatory and audit deliverables, including capital stress testing. The MRGR Product Team handles technology and analytics coordination, while the MRGR Analytics Team develops supplemental tools and supports independent testing. The MRGR Reporting & Execution Team bridges MRGR COO and LOB-aligned teams, and the MRGR Regulatory & Audit Team oversees regulatory deliverables. The MRGR Business Management Team manages budgeting, headcount, and internal training, ensuring financial discipline and effective communication.
The main requirements for this team are:

  • Bachelor's or Master's degree in a STEM discipline with significant programming exposure.
  • Experience in full-stack application development
  • Proficiency in Python and knowledge of Tornado web framework, TypeScript, or React


or

  • Bachelor's degree in a relevant field (e.g., Communications, Engineering, Finance, Accounting, Economics, Mathematics).
  • Experience in financial services, business management, or related fields.


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.

Top Skills

C++
Matlab
Python
R

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