Algorithmic trading automaton - C++ Quantitative Developer

The Trading Core & Model Technology team builds and maintains the core software infrastructure that powers systematic execution strategies, which consists of:

• C++ applications managing trading automatons and feed handlers.
• Python data pipelines generating referential data for the automatons and execution cost reports.
• A machine learning pipeline used for execution strategies.

CFM is looking for an experienced and talented Quantitative Developer to maintain these real-time C++ applications, and deliver enhancements tailored to the needs of the execution research team., As a Quantitative Developer, you will be responsible for:

1. developing and maintaining these real-time C++ applications: new features, optimizations, fixing bugs and providing level 2 support.
2. Working closely with researchers to actively identify their pain points and requests, addressing them through high-quality solutions, communicating with them efficiently and managing their expectations.

Do you have experience in Python?, Do you have a Master's degree?, * Bachelor's or Master's degree in Computer Science or a related field.

• Expertise in the development of real-time, low latency, C++ market data systems and/or algorithmic trading automatons.
• A minimum of three years of experience in such a role is required but candidates with significantly more experience will be considered with great interest.
• Excellent collaboration and communication skills.
• Adaptable and rigorous, capable of working in a rapidly evolving environment.
• Proficiency in both French and English.

Founded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients. We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.