Quantitative Developer

Our client is looking for an experienced Quantitative Developer to join a specialised Front Office Quant team focused on the development and enhancement of Counterparty Credit Risk (CCR) and XVA models. In this role, you will contribute to the full lifecycle of in-house pricing and risk models, from quantitative model design and prototyping through implementation, optimisation and production support. Your primary focus will be the development and enhancement of models used for Potential Future Exposure (PFE) and Exposure at Default (EAD) calculations. You will also contribute to the development of a high-performance computing platform supporting pricing and risk management. Working closely with traders, risk managers, model integration teams and fellow quantitative developers, you will deliver robust quantitative solutions using modern software engineering practices within an Agile (Scrum) environment. This is an excellent opportunity for someone who combines strong quantitative modelling expertise with advanced software engineering skills., As a Quantitative Developer, you will:

• Design, develop and enhance Counterparty Credit Risk models for PFE and EAD calculations.
• Develop, implement and maintain pricing and risk models throughout their full lifecycle.
• Contribute to the development and optimisation of a high-performance C++/CUDA computing platform.
• Collaborate with Front Office model integration teams to deploy quantitative models into production.
• Develop high-quality software following Agile (Scrum) methodologies and software engineering best practices.
• Work closely with quantitative analysts, traders, risk managers and technology teams.
• Provide quantitative support and expertise to Front Office stakeholders.
• Contribute to continuous improvements in modelling frameworks, performance and code quality., * Opportunity to work on complex quantitative models used in Front Office risk management.
• Collaboration with highly skilled quantitative and technology professionals.
• Exposure to modern software engineering practices and high-performance computing technologies.
• A dynamic, Agile working environment with long-term project opportunities.

You are an experienced quantitative professional with a strong background in financial modelling, software development and Front Office risk management. You bring:

• At least 5 years of experience in quantitative modelling within Counterparty Credit Risk and/or Market Risk.
• Strong experience with Monte Carlo simulation, derivatives pricing and risk factor modelling.
• Expertise in one or more asset classes such as Interest Rates, FX, Credit, Commodities, Equity or XVA.
• Strong programming skills in Python and/or C++, preferably within Front Office environments.
• A Master’s or PhD degree in Mathematics, Physics, Statistics, Econometrics, Computer Science, Engineering or a related quantitative discipline.
• Experience with professional software development practices, including Test-Driven Development (TDD), Continuous Integration (CI) and Continuous Delivery (CD).
• Experience with Azure, Git and Docker is considered an advantage.
• Excellent communication skills in English.

Everience is an international consulting group delivering AI-augmented digital services and placing people at the heart of the AI revolution. With a presence in Europe, Africa, Asia and America, Everience offers its 4,000-strong workforce the most demanding and stimulating environment in which to transform and develop their skills, learning about new AI-based roles and building their future employability. Through its Symbiotic Academy the group offers a unique hub for training, practical application and exchange where everyone can experiment, learn, and progress in the fields of artificial intelligence and data. In accordance with its core purpose of orchestrating the symbiotic relationship between humans and AI in the workplace, Everience is making the augmented employee the driving force of a “symbiotic age”, where AI enhances talents and opens up new career opportunities.