Senior Quantitative Analyst

Magnit Global; Greater London; Hybrid; GBP 147,000 - 193,000; Full time

Job summary

Global Banking Organisation in London seeks an experienced Quantitative Model Validation specialist to join its Model Risk Management function. You will validate models focusing on PFE, CCR and XVA, while developing challenger models and reviewing mathematical frameworks.

You will collaborate with Front Office Quants and Risk Analytics, perform Monte Carlo testing, and produce detailed validation reports for governance committees.

Qualifications

• 2 years' experience with XVA or related models.
• Strong understanding of CCR, derivatives pricing and/or PFE modelling.
• Advanced knowledge of mathematical finance, probability, statistics and numerical methods.
• Experience with Monte Carlo simulation and numerical risk modelling.
• Postgraduate qualification in a quantitative discipline.
• Experience in Model Validation or Model Risk Management.
• Knowledge of CVA, DVA, FVA and other XVA methodologies.
• Experience developing models in Front Office or Risk Analytics.
• Programming experience with C++ or C#.
• Familiarity with Basel regulatory capital and CCR frameworks.
• Exposure to AI or ML models.

Responsibilities

• Perform independent validation of quantitative models focusing on PFE, CCR and XVA.
• Develop challenger models to assess accuracy of existing methodologies.
• Review modelling frameworks, inputs, assumptions and outputs.
• Conduct quantitative testing using Monte Carlo and numerical methods.
• Reproduce model calculations and investigate discrepancies.
• Review pricing and counterparty exposure methodologies across asset classes.
• Assess models against governance standards and regulatory requirements.
• Produce detailed model validation reports with findings and recommendations.
• Engage with Front Office Quants, Risk Analytics and model developers to drive improvements.
• Present validation findings to senior stakeholders and governance committees.

Skills

XVA modelling

PFE modelling

CCR modelling

Monte Carlo methods

CVA modelling

Model validation

Risk analytics

Quantitative risk management

C++/C#

Regulatory capital knowledge

AI/ML exposure

Education

Postgraduate degree in Mathematics/Financial Engineering/Statistics/Physics

Tools

C++

C#

Job description

Global Banking Organisation

London | 3 days in the office

£920 per day inside IR35 | 6 month contract

We are currently recruiting for an experienced Quantitative Model Validation specialsit to join the Model Risk Management function of a leading global investment bank in London.

This is an excellent opportunity for a technically strong Quantitative Analyst or Model Validation specialist with expertise in Counterparty Credit Risk (CCR), Potential Future Exposure (PFE) and XVA modelling.

Key Responsibilities:

• Perform independent initial and periodic validation of quantitative models, with particular focus on PFE, CCR and XVA.
• Develop, implement and test independent challenger models to assess the accuracy and robustness of existing methodologies.
• Review mathematical frameworks, modelling assumptions, statistical techniques, data inputs and model outputs.
• Conduct quantitative testing using simulation and numerical methods, including Monte Carlo techniques.
• Independently reproduce model calculations and investigate discrepancies or potential weaknesses.
• Review derivatives pricing and counterparty exposure methodologies across different asset classes.
• Assess models against internal governance standards, regulatory requirements and industry best practice.
• Produce detailed model validation reports, documenting findings, limitations and recommendations.
• Engage directly with Front Office Quants, Risk Analytics and model development teams to challenge methodologies and drive improvements.
• Present validation findings and model risk assessments to senior stakeholders and governance committees.

Experience Required:

We are looking for candidates with a strong quantitative background gained within an investment banking or financial services environment.

• At least 2 years' experience working with XVA or closely related quantitative models.
• Strong understanding of Counterparty Credit Risk, derivatives pricing and/or PFE modelling.
• Advanced knowledge of mathematical finance, probability theory, statistics and numerical methods.
• Strong understanding of Monte Carlo simulation, numerical modelling and quantitative risk methodologies.
• Experience assessing model assumptions, limitations, implementation accuracy and model performance.
• Postgraduate qualification in Mathematics, Financial Engineering, Mathematical Finance, Statistics, Physics or a related quantitative discipline.
• Previous experience within an independent Model Validation or Model Risk Management function.
• Strong working knowledge of CVA, DVA, FVA and other XVA methodologies.
• Experience developing quantitative models within Front Office or Risk Analytics teams.
• Programming experience with C++ or C#.
• Knowledge of Basel regulatory capital requirements and counterparty credit risk frameworks.
• Exposure to AI or machine learning models.