Quantitative Developer

Bonhill Partners; England; On-site; GBP 70,000 - 90,000; Full time

Job summary

An investment banking consultancy is looking for a Quant Engineer in London to enhance their core team. The role involves developing production systems and quantitative models, requiring strong experience in C# or C++. Candidates should have a solid quantitative background, knowledge of rates, FX, inflation, and credit, and experience in a front-office environment. This is a 6-month rolling contract role with a requirement for 5 days in the office.

Qualifications

• Proven experience in C# or C++ for production systems.
• Ability to design scalable systems and APIs.
• Quantitative skills with a solid understanding of mathematical modeling.

Responsibilities

• Design, implement, and maintain production components in C# or C++.
• Contribute to high-performance system design.
• Develop and validate pricing and risk models.

Skills

Strong production experience in C# or C++

Experience designing scalable systems and APIs

Strong quantitative background

Product knowledge across rates, FX, inflation, and credit

Experience in front-office environments

Job description

Bonhill Partners are currently supporting an Investment Bank based in London to expand their core Quant engineering team contributing to the development of production systems, quantitative models, and tools used across the business.

Client: Investment Bank

Contract Duration: 6 Months Rolling

Location: London, (5 Days in Office)

Requirements

• Strong production experience in C# or C++.
• Experience designing scalable systems and APIs.
• Strong quantitative background and comfort with mathematical modelling.
• Product knowledge across rates, FX, inflation, and credit.
• Experience in front-office or front-office-adjacent environments is beneficial.

Responsibilities

• Design, implement, and maintain robust production components in C# or C++.
• Lead or contribute to scalable, maintainable, high-performance system and API design.
• Develop, extend, and validate pricing and risk models.
• Incorporate product knowledge across multiple asset classes into model behaviour and system architecture.
• Collaborate with trading, Product Control, Model Validation, and engineering teams.