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| Job Location | London |
| Education | Not Mentioned |
| Salary | Competitive salary |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Permanent, full-time |
Volatility Systematic Trading Quant Research - VP level London and Paris based This group is looking for a quant for the Equity Derivatives Flow business. The groups broad objective is to drive and implement the automation and optimization of volatility trading, including client trade pricing and hedging, managing risk and electronic execution and market making. The role should contribute to all these aspects, making extensive use of data and quantitative techniques, including machine learning. The successful candidate will be business driven, have previous quantitative experience in a Bank or Hedge Fund, ideally in the equity option markets, strong knowledge of statistical methods, risk and alpha modelling, solid expertise in programming languages (python, KDB, java), as well as excellent communication skills. Responsibilities: Work on the Equity Derivatives Flow trading desk to build trading algorithms, analytics and processes that automatize and optimize trading; Build data-driven trading algorithms for quoting and hedging derivatives client trades and managing the risks. Optimize delta hedging. Build systematic strategies trading options and other volatility products. Build efficient electronic option execution and market making algorithms. Optimize trading with high to low frequency alpha signals; Contribute from idea generation to production implementation: perform research, design prototype, implement analytics and trading algorithms to manage client flow and risk inventory, support their daily usage and analyse their performance. Requirements: Strong graduate degree (MS, PhD or equivalent) in a quantitative field (Mathematics, Physics, Statistics, Quantitative Finance, Economics, Computer Science, etc.); Experience in equity derivatives, including electronic option trading and volatility alpha strategies (high to low frequency); Strong knowledge and practice of derivatives pricing models and hedging techniques. Experience working with high frequency market data and back testing. Working knowledge of statistics and machine learning in financial industry; Strong programming in Python, KDB, C++. Ability to handle and analyse complex, large scale, high-dimensionality data from varying sources; Business driven, excellent communication, deep interest in the option business, electronic trading and automation. Entrepreneurial spirit, strong attention to details, able to take the lead on projects, and passion for spreading a culture of change towards data-driven trading.