Cross-Asset Quantitative Analyst, Global Asset Manager, London, London

Responsibilities

• Research and build quantitative trading and screening models
• Source, test and integrate new signals into existing frameworks
• Monitor and distribute trade ideas generated by quant tools
• Deliver standalone research with concise reports and presentations
• Provide thematic quantitative research and thought leadership
• Enhance the research platform and shared codebase
• Improve dissemination and visualisation of model outputs
• Uphold robust coding standards, version control and testing
• Communicate model insights to Portfolio Managers, Analysts, Traders and Investment Directors
• Support internal and external positioning of the quant team
• Participate in cross-asset team meetings and collaborate across regions
• Engage with clients as required

Requirements

• BSc/MSc in a quantitative field with knowledge of statistics, econometrics and numerical methods
• Practical experience developing quantitative models for investment
• Strong Python programming (pandas, NumPy); SQL and Git advantageous
• Proficient with Excel; familiarity with Bloomberg desirable
• Experience handling and analysing large datasets
• CFA or equivalent evidence of market knowledge is a plus
• Clear written and verbal communication skills
• Collaborative mindset and ability to work across functions