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Job Title: Quantitative Researcher - Systematic Volatility Team
Location & Availability:
•Paris-based, situated at the heart of one of the world's leading financial centres.
Education:
•Graduated from a Top Tier School, renowned for its rigorous academic standards and excellence in quantitative disciplines, such as:
•PhD preferred, especially in Statistics or Machine Learning, demonstrating a commitment to advanced research methodologies.
Experience:
•3 to 8 years of progressive experience in quantitative research, ideally within a financial institution or a leading research organization.
•Strong familiarity with statistical analysis and machine learning techniques.
•Prior exposure to financial markets preferred, with a focus on volatility strategies and risk management principles.
•While financial experience is preferred, exceptional candidates without specific finance backgrounds will also be considered, especially those demonstrating strong quantitative research skills.
Coding Skills:
•Mastery of Python programming language, considered essential for conducting quantitative research and implementing trading strategies.
•Willingness to learn and adapt to proprietary quantitative software suite for backtesting & financial analysis, indicative of a proactive approach to skill development and technological innovation.
Mission:
•Join the dynamic and innovative systematic volatility team within our Equity Volatility RV pod, led by a seasoned senior partner.
•Collaborate closely with multidisciplinary teams to conduct cutting-edge quantitative research and develop sophisticated trading strategies.
•Engage with strategy teams and senior stakeholders to align research objectives with business goals and market dynamics.
•Spearhead research initiatives aimed at enhancing the pod’s quantitative alpha framework, encompassing feature engineering, predictor development, and optimization of investment policies.
•Drive innovation by exploring and developing novel systematic volatility trading strategies, leveraging the latest advancements in quantitative finance and machine learning.
•Contribute actively to the development and refinement of the pod’s dynamic portfolio construction engine, ensuring robust risk management practices and optimal portfolio performance.
Key Responsibilities:
•Conduct rigorous quantitative research to generate actionable insights and alpha-generating strategies.
•Collaborate closely with team members to translate research findings into systematic trading models, ensuring scalability and efficiency in implementation.
•Continuously evaluate and enhance existing trading strategies, leveraging empirical analysis and quantitative techniques.
•Contribute to the development of risk models and methodologies, providing insights into portfolio construction and optimization.
•Stay abreast of the latest developments in quantitative finance, machine learning, and financial markets, actively contributing to the intellectual capital of the team and the organization.
