Within the Core Investments platform (gathering Equities / Fixed Income / Multi-Asset expertises), the Quant Lab teams provide a number of quantitative services, among which strategic asset allocations recommendations, tactical asset allocation portfolio construction and risk analysis, or the development of a library of pricing and simulation functions.
The recruited person will work side by side with 3 teammate data scientists within the Quant Lab. The main focus for this position is to expand the Quant Lab’s coverage to the field of investment signals. In that context, main responsabilities will be: (I) to work hand by hand with portfolio managers and economists to develop quantitative investment signals supported by strong data-driven evidence and a financial rationale; (II) to explore to what extent data science methods might improve the quality of signals compared to more standard econometric and statistical techniques; (III) to share knowledge and findings on investment signals with the other data scientists to gradually embark them in the signals development initiative; (IV) to integrate the quantitative signals research framework into a common powerful data science platform.
• Work hand by hand with portfolio managers and economists to develop quantitative investment signals across cash and derivatives markets
• Proactively propose new quantitative alpha signals and improve existing methods for signals construction
• Develop a proper investment signals research framework, from clean data sourcing to robust testing and validation protocols to seamless update and production capabilities
• Document investment signals research and share knowledge and findings across the Core Investments platform
• More broadly, take part to internal discussions about data science usage and framework, and proactively contribute to the internal ‘Accelerate Data Science’ community
Skills and Experience:
• Advanced knowledge of econometrics and standard financial statistical methods
• Understanding of financial markets, macroeconomics, investment strategies, different asset classes, types of investment vehicles, and derivatives
• Knowledge of Python or R as a scientific programming language
• Advanced degree in a quantitative discipline (Economics, Finance, Applied Mathematics, Statistics)
• CFA charterholder is an advantage
• Strong quantitative skills and understanding of advanced applied statistics
• Excellent communication skills in English
• Second European language, in particular French, is an advantage
• Attention to details
• Ability to multitask and keep calm under pressure
• Advanced presentation skills.
• Team player, collaborative
• Excellent interpersonal skills
• Integrity and honesty are a must