Hybrid Quant Modelling Director – Front Office

I’m partnering with a leading investment bank on a Director-level opportunity within its Front Office Quantitative Analytics function.

This is a strategic technical leadership role focused on leading the review, challenge and continuous improvement of pricing models across a global Front Office platform. Rather than focusing on a single asset class, you’ll work across Rates, FX, Equity, Credit and Hybrid Derivatives, partnering with specialist quant teams to drive pricing model quality, governance and consistency.

A key part of the role is acting as the technical lead for Hybrid Derivatives and cross-asset pricing models, including products where payoffs depend on multiple asset classes, as well as pricing models that incorporate multiple asset classes.

The Role:

Working closely with Front Office Quantitative Analytics, Trading, Quant Development, Model Validation, Risk, Finance, Technology and Control functions, you will:

• Lead the Front Office Model Review capability across multiple asset classes.
• Provide independent challenge by reviewing pricing models and modelling approaches across the Front Office.
• Act as the technical lead for Hybrid pricing and adjustment models.
• Drive pricing model quality, governance and consistency throughout the model lifecycle.
• Review, challenge and enhance pricing methodologies and calibration approaches, helping shape the evolution of the firm’s pricing framework.
• Oversee model submissions, functional testing and governance reviews across multiple asset classes.
• Develop and enhance model review methodologies, standards and best practices.
• Partner with specialist quant teams to improve pricing models, implementation and technical solutions.
• Drive automation and tooling to improve model review and testing processes.
• Influence senior Front Office stakeholders and help shape the future direction of pricing models across the business.

While this isn’t a pure model development role, you’ll remain close to the technical detail. The emphasis is on applying strong quantitative judgement to review existing models, challenge assumptions, improve methodologies and calibration, and influence the design and evolution of pricing models across multiple asset classes.

Although this isn’t a traditional people management role initially, it is a highly visible technical leadership position for someone with the credibility to become a recognised authority across the Front Office quantitative environment. You’ll lead model review across asset classes, influence pricing model quality and help shape future methodologies, standards and automation capabilities.

We’re looking for candidates with experience in:

• Front Office Quantitative Analytics.
• Pricing model development, model validation, review or governance.
• Rates, FX, Equity, Credit or Hybrid Derivatives.
• Hybrid or cross-asset pricing models.
• Strong understanding of pricing models, calibration and model methodologies across multiple asset classes.
• Experience reviewing, challenging or testing pricing models.
• Python is preferred, although strong modelling experience in another language will also be considered. C++ is beneficial but not essential.

Exposure to areas such as model testing frameworks, valuation adjustments (FVA/PVA), automation, AI-enabled tooling or governance frameworks would be advantageous but isn’t essential.

This is a unique opportunity to influence how pricing models are reviewed, governed and evolved across a global Front Office platform, working alongside senior quantitative teams across multiple asset classes and helping shape the future direction of pricing model quality, quantitative governance, methodology and technical standards.

Get in touch to discuss further – tg@barclaysimpson.com

We seek individuals from a diverse talent pool and encourage applicants from underrepresented groups to apply to our vacancies. Our commitment to fair recruitment processes means that we welcome applicants from all backgrounds, regardless of their lived experience or personal characteristics. We also invite applicants who meet most of the listed requirements, even if not all, to apply. If you require any adjustments to the application process, please let us know.

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