Quant Modeling Analyst

JPMorganChase; London; On-site; GBP 60,000 - 90,000; Full time

Job summary

Join a leading financial services firm as a Quant Modeling Analyst in the Model Risk Governance and Review group. You will assess and mitigate model risks for electronic trading and strategic indices. Collaborate with developers and users to ensure model integrity and compliance. This role demands strong analytical skills, a relevant advanced degree, and proficiency in programming languages. Be part of a dynamic team committed to excellence in risk management and model governance.

Qualifications

• Master’s or PhD in relevant fields required.
• Strong analytical and problem-solving skills needed.

Responsibilities

• Evaluate model specifications and assumptions.
• Perform independent testing of models.
• Document review findings and communicate with stakeholders.

Skills

Analytical Skills

Problem-Solving

Communication

Education

Master’s or PhD in Mathematics

Master’s or PhD in Physics

Master’s or PhD in Engineering

Master’s or PhD in Computer Science

Master’s or PhD in Economics

Master’s or PhD in Finance

Tools

C/C++

Python

NumPy

SciPy

Pandas

TensorFlow

SQL

kdb

q

Job description

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Job Description

We are looking for a new member to join our cross-asset team in the Model Risk Governance and Review group, responsible for end-to-end model risk management across the firm for electronic trading, strategic indices, and prime services models.

As a Quant Modeling Analyst, you will assess and help mitigate the model risk of complex models used in valuation, risk measurement, capital calculation, and decision-making. You will work closely with model developers and users across various business and functional areas.

Job Responsibilities

1. Evaluate the conceptual soundness of model specifications, assumptions, input reliability, testing completeness, implementation correctness, and performance metrics.
2. Perform independent testing by replicating or building benchmark models.
3. Design experiments to assess model limitations, parameter estimation errors, and deviations from assumptions; compare outputs with empirical data or benchmarks.
4. Evaluate risks from non-transparent parameters and non-linear relationships; suggest mitigation strategies.
5. Document review findings and communicate to stakeholders.
6. Serve as the primary contact for model governance inquiries and escalate issues as needed.
7. Guide model developers and users on appropriate model usage.
8. Monitor and communicate ongoing model performance testing outcomes.
9. Maintain the model inventory and metadata.
10. Stay updated on developments in products, markets, models, and industry standards.

Required Qualifications, Capabilities, and Skills

• Master’s or PhD in Mathematics, Physics, Engineering, Computer Science, Economics, or Finance.
• Strong analytical and problem-solving skills.
• Expertise in probability theory, stochastic processes, statistics, PDEs, and numerical analysis.
• Risk-aware mindset: ability to ask incisive questions, assess materiality, and escalate issues.
• Excellent written and verbal communication skills.
• Understanding of option pricing theory and derivatives models.
• Proficiency in coding (e.g., C/C++, Python).

Preferred Qualifications, Capabilities, and Skills

• Experience with data and numeric programming (NumPy, SciPy, Pandas).
• Knowledge of database interfacing and data management (kdb, q, SQL).
• Experience with machine learning packages like TensorFlow.

About Us

J.P. Morgan is a global leader in financial services, providing strategic advice and products worldwide. We value diversity and are committed to equal opportunity employment.

About The Team

J.P. Morgan’s Commercial & Investment Bank offers banking, markets, securities services, and payments across more than 100 countries, serving corporations, governments, and institutions.