Quantitative Volatility Researcher

Quantitative Volatility Researcher A small, collaborative, and entrepreneurial investment team is seeking a Quantitative Volatility Researcher to be responsible for researching, developing and implementing quantitative models and strategies to analyze and exploit market volatility within equities. This role is ideal for somebody with a strong background in quantitative finance, mathematics or a related filed, who is passionate about contributing to the growth and success of the team. Principal Responsibilities Work in core volatility alpha research team on conducting quantitative research on market volatility, focusing on development of models and strategies to predict and exploit movements in various asset classes (primarily equities). Primary focus will be on: idea generation, data gathering and research/analysis, model implementation and build tools for timeseries analysis, optimization and backtesting Conduct research on global systematic option markets, with a focus on single stocks vs index spreads and selected bespoke ETFs, to generate signals Combine sound financial insights and statistical learning techniques to explore, analyze, and harness a large variety of datasets in order to build strong predictive models which will be deployed to the investment process Collaborate with trading pods to integrate research findings into the investment strategies and risk management process Develop and maintain tools and software to support research and trading activities across different trading pods Preferred Technical Skills Master’s, or PhD degree in Quantitative Fields such as Computer Science, Engineering, Applied Mathematics, Statistics, Physics or related disciplines. Deep knowledge of financial markets and instruments, particularly options and other derivatives Excellent communication, analytical, and problem-solving skills Preferred Experience Minimum of 3 years of experience working on Quantitative Vol research projects / tools Experience working with large and diverse data sets and in a data-driven research environment Highly Valued Relevant Experience Experience with machine learning, statistical analysis, data visualization techniques Python programming skills a must Knowledge of Asia EQ derivatives markets and relevant vol fitting /analytics a huge plus

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