Quant Risk Analyst - CCR - Contract - Inside IR35 - London - Investigo

eFinancialCareers; Greater London; Hybrid; GBP 111,000 - 166,000; Full time

Job summary

eFinancialCareers in London is seeking a Contract Quantitative Analyst to join its Risk Analytics function, focusing on Counterparty Credit Risk methodologies across asset classes.

The role involves developing exposure models, calibrating PFE and EE, and collaborating with Risk, Front Office, Technology and Validation teams in a hybrid London setup. Ideal candidates will have strong Python, Monte Carlo experience and advanced quantitative qualifications.

Qualifications

• Experience in Counterparty Credit Risk and exposure modelling.
• Strong background in PFE/EE and derivatives pricing.
• Proven ability to validate models and communicate results.

Responsibilities

• Develop, maintain and enhance counterparty exposure models.
• Support methodologies covering PFE, EE and stressed exposure measures.
• Perform model calibration, testing, performance analysis and backtesting.
• Investigate model issues and implement enhancements for robustness.
• Prepare governance reporting and collaborate with stakeholders.

Skills

Counterparty Credit Risk

Exposure Modelling

PFE

EE

Derivatives pricing

Quantitative risk modelling

Python

Monte Carlo

Model validation

Statistics

Education

MSc in Quantitative Finance

PhD in a quantitative field

CQF

FRM

Job description

Contract Quantitative Analyst - Counterparty Credit Risk (CCR)

London | Hybrid (3 Days Office) | Contract

A leading global banking group is seeking a Contract Quantitative Analyst to join its Risk Analytics function, supporting the development and enhancement of Counterparty Credit Risk methodologies across a broad range of asset classes.

This is a highly visible role sitting within a specialist quantitative team responsible for exposure modelling, model performance, governance and strategic risk analytics initiatives. The successful candidate will work closely with Risk, Front Office, Technology and Model Validation teams.

Responsibilities

• Develop, maintain and enhance counterparty exposure models.
• Support methodologies covering Potential Future Exposure (PFE), Expected Exposure (EE) and Stressed Exposure measures.
• Perform model calibration, testing, performance analysis and backtesting.
• Investigate model issues and implement enhancements to improve robustness and accuracy.
• Support new product onboarding into the risk framework.
• Work with technology teams on model and system implementation changes.
• Address model validation findings and regulatory requirements.
• Prepare management reporting and contribute to governance forums.
• Support business stakeholders with quantitative analysis and exposure-related investigations.
• Contribute to strategic risk and modelling projects across the wider Risk function.

Required Experience

• Strong background in Counterparty Credit Risk, Exposure Modelling, xVA, Quantitative Risk or Model Validation.
• Experience working within investment banking or capital markets environments.
• Strong understanding of: Potential Future Exposure (PFE)
• Strong understanding of: Expected Exposure (EE)
• Strong understanding of: Counterparty Credit Risk methodologies
• Strong understanding of: Derivatives pricing principles
• Strong understanding of: Quantitative risk modelling techniques
• Experience with Monte Carlo simulation frameworks.
• Strong Python programming skills.
• Excellent understanding of probability, statistics and stochastic processes.
• Ability to explain model design, assumptions, calibration approaches and limitations in detail.

Preferred Experience

• Initial Margin or SIMM modelling.
• Securities Financing Transactions (SFTs).
• Exposure modelling across Rates, FX, Credit, Inflation or Equities.
• Knowledge of C++ or C#.
• Advanced quantitative qualifications (MSc, PhD, CQF, FRM or similar).

Candidate Profile

This opportunity would suit a hands-on quantitative analyst who enjoys owning models throughout their lifecycle, from development and calibration through validation, governance and ongoing enhancement.