Quanteam is recruiting on behalf of a prestigious global quantitative investment firm, recognized for operating across all major liquid asset classes worldwide. Our client is a technology-first, data-driven organization applying a rigorous scientific approach to investing through cutting-edge research, advanced engineering, and high-performance trading infrastructure.

This is a rare opportunity to join a firm known for its innovation culture, collaborative mindset, and world-class quantitative research environment.

The role:

As part of a cross-functional team, providing valuable business support across a variety of areas, including:

• Trading support: ensuring accurate and appropriate analysis and reporting of PnL and positions
• Enriching internal python codebase with production standard code for trading monitoring and reporting
• Ensure maintenance and support of global reporting systems, including interactions with EMEA teams
• Production of daily reports and dashboards for management
• Managing corporate actions, resolution of booking issues
• Modelling and analysis of performance attributes per strategy/instrument
• Performing ad-hoc analysis

The requirements:

• 1-5 years of relevant work experience
• An advanced degree in business or engineering with a specialism or focus in banking/finance
• Proficiency in Python and SQL is required.
• Proficiency in C# is a plus.
• Knowledge in Probability and Statistics is an advantage
• Advanced knowledge of MS Office tools
• Capacity to adapt and multi-task in a fast-paced environment while maintaining attention to detail
• Good organizational and analytical skills
• Good oral and written communication skills
• Team player

Learning Opportunities:

• Mentorship from industry professionals
• Detailed practical hands-on experience with software
• Exposure to large scale data analysis technology
• Experience in a collaborative and collegial corporate environment
• Collaborating with multiple stakeholders: traders, quant researchers, operations, risk managers, IT etc.

The client's identity will be shared with shortlisted candidates.