Front Office Quant IV

Role overview

You will work as a Front Office Quant Developer focused on quantitative modelling, particularly within Counterparty Credit Risk (CCR). The role emphasizes model design, prototyping and implementation for Front Office pricing and risk systems, with a focus on Potential Future Exposure (PFE) and Exposure at Default (EAD). The modelling environment includes Monte Carlo modelling, derivatives pricing, risk factor modelling and multiple asset classes (e.g. FX, Equity, SFT).

Responsibilities

• Design and enhance Counterparty Credit Risk models for PFE and EAD.
• Work hands-on across the quantitative model lifecycle from design and prototyping to implementation.
• Develop and work with Monte Carlo models, risk factor models and derivatives pricing models.
• Apply quantitative models across different asset classes.
• Implement quantitative models using Python and/or C++ for Front Office purposes.
• Contribute to high-performance computing platforms (C++/CUDA) used for pricing and risk management.
• Collaborate with quantitative colleagues and IT model integration teams.
• Provide quantitative support to risk managers, traders and other stakeholders.

Requirements

• Education: University degree in Mathematics, Physics, Statistics/Econometrics, Computer Science, Engineering or another relevant quantitative discipline; MSc or PhD preferred.
• Experience: At least 5 years of Quant experience within Counterparty Credit Risk and/or Market Risk modelling.
• Strong hands-on quantitative modelling background with specific relevance to the CCR domain.
• Professional experience with Monte Carlo modelling, risk factor modelling and derivatives pricing.
• Experience with at least one relevant asset class or modelling area (Interest Rates, FX, Commodities, Credit, Equity or XVA).
• Proven ability to implement quantitative models in Python and/or C++ for Front Office use.
• Familiarity with professional software-development practices (Test-Driven Development, Continuous Integration/Delivery).
• Fluent English and ability to communicate effectively with technical and non-technical stakeholders.

Preferred experience

• Experience with Azure, Git and Docker.
• Experience across multiple asset classes, including FX, Equity and SFT.

Profile fit

This is a quantitative modelling role with a significant technical implementation component. The primary focus is not pure software engineering. The strongest fit is an experienced Quant who combines deep hands-on CCR modelling experience with sufficient programming capability to implement models in a Front Office environment.

Eisen

• University degree in Mathematics, Physics, Statistics/Econometrics,
  Computer Science, Engineering or another relevant quantitative discipline
• At least 5 years of Quant experience within Counterparty Credit Risk and/or
  Market Risk modelling
• Strong hands-on quantitative modelling experience, with particular
  relevance to the CCR domain
• Professional experience with Monte Carlo modelling, risk factor modelling
  and derivatives pricing
• Experience with at least one relevant asset class or modelling area, such
  as Interest Rates, FX, Commodities, Credit, Equity or XVA
• Strong background implementing quantitative models in Python and/or C++
  for Front Office purposes
• Experience with professional software-development practices including
  Test-Driven Development, Continuous Integration and Continuous Delivery
• Fluent English and the ability to communicate effectively with both
  technical and non-technical stakeholders

Wensen

• MSc or PhD is preferred
• Experience with Azure, Git and Docker is preferred
• Experience across multiple asset classes, including environments involving
  FX, Equity and SFT, is relevant to the work of the team

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