Are you passionate about derivatives trading, data statistical modelling and algorithms? Join our Systematic Trading Quantitative Research APAC team and lead the trading transformation through modern data-driven techniques and automated decision processes. This is an exciting opportunity to design innovative trading strategies and make your mark in the volatility trading space.
As a Vice President/ Executive Director in the QR Systematic Trading APAC group, you will partner with equity derivatives flow traders and market makers to develop data-driven trading signals, combine those alphas with cost and risk models into systematic strategies (mostly mid frequency), optimize portfolio allocation across multiple strategies, and integrate those trading strategies into automated trading processes or trading algorithms. Communication skills and drive are critical for this role as we expect the candidate to actively engage with the business and be a culture carrier to promote automated trading in the equity derivatives space.
Job Responsibilities
- Work closely with our equity volatility flow and market making desks to identify new business opportunities and approach those with an industrial and systematic mindset
- Contribute to the entire lifecycle from idea generation to live trading: conceptualisation and formalisation, alpha / strategy research, implementation, daily monitoring and ongoing performance analysis
- Automate and optimize derivatives trading quantitatively. This includes: industrial alpha research for volatility, optimal strategy allocation across option portfolios, listed option algorithmic execution, derivatives market making, volatility analytics
- Partner with other businesses such as Cash and Prime Finance to develop synergies in the quantitative trading space (research platform, mandates, data)
Required Qualifications, Capabilities, and Skills
- PhD or Master’s Degree in a quantitative discipline from a top-tier institution
- Experience in systematic quantitative trading in Equity or related asset classes
- Strong written and verbal communication skills, ability to convey the ideas behind complex research in a clear and precise manner
- A thorough understanding of algorithmic trading, market making and statistical arbitrage
- Good expertise in statistical modelling & optimization, including standard models, linear, convex & conic optimization
- A strong coding background with proficiency in Python and relevant quantitative packages (numpy, pandas, …)
- Ability to manipulate and analyse complex, large scale, high-dimensionality data from multiple sources
Preferred Qualifications, Capabilities, and Skills
- Knowledge of KDB/Q and prior experience with KDB ecosystem strongly favoured
- Solid understanding of derivatives pricing, risk management theory (vanilla options and volatility products) and risk metrics (e.g. VaR, CVaR, …)
- Proficiency in numerical computing such as JAX for high-performance array operations and automatic differentiation in ML models, or Tensorflow / PyTorch for building and trading deep learning networks
- Exposure to GPU-accelerated computing
- Experience with additional programming languages such as C++