Description

An exciting opportunity has opened for a Junior Quantitative Developer to join a leading global trading and technology team based in Geneva . This role is ideal for someone with a strong foundation in software engineering who enjoys working with complex systems and applying quantitative methods to real-world financial challenges.

You will play a key role in developing and refining the infrastructure behind large-scale algorithmic trading operations, collaborating with quantitative researchers, technologists, and portfolio teams to deliver high-performance solutions that enable cutting-edge research and live trading execution.

This position offers the chance to work at the intersection of technology and finance , in an intellectually stimulating and collaborative environment where innovation and technical excellence are valued.

What You'll Do

• • Design, develop, and enhance the firm's research and trading systems.
  • Ensure the platform delivers scalability, reliability, and ultra-low latency for large volumes of market data and transactions.
  • Collaborate with quantitative researchers to validate model performance in both simulation and live environments.
  • Automate processes to streamline research, testing, and deployment workflows.
  • Promote best practices in coding, testing, and model design.
  • Contribute directly to core development using Python and Java .

What We're Looking For

Essential Skills & Experience

• • At least 2 years' experience in a quantitative development, software engineering, or similar technical role.
  • Strong, practical programming skills in Python and Java (hands-on coding and debugging experience required).
  • Solid understanding and daily use of Linux environments.
  • Familiarity with cloud computing , distributed systems , and containerization tools (e.g., Docker, Kubernetes).
  • Experience using version control and continuous integration tools (e.g., Git, Jenkins).

Desirable Skills

• • Knowledge of system performance optimization (profiling, caching, time complexity, memory management).
  • Exposure to machine learning frameworks or optimization libraries (e.g., Mosek).
  • Understanding of financial instruments , market data, and pricing models.

Education

• • Degree in Computer Science, Mathematics, Physics , or another technical discipline with strong quantitative content.