• CDI, Plein-temps
  • Anson McCade
  • 2018-06-22
  • Londres, Angleterre, Royaume-Uni
  • Competitive
  • Plein-temps

Equity Quantitative Research – Systematic Trading – VP level

The primary aim of this team is to research and develop quantitative models for the Equity Derivatives business, as well as to ensure their compliance with internal policies and industry regulations. This will be sitting in the Equity Quantitative Research team, focusing on quantitative strategies and the optimization of trading for the Equities desks.

Equity Quantitative Research – Systematic Trading – VP level

London based

 

The primary aim of this team is to research and develop quantitative models for the Equity Derivatives business, as well as to ensure their compliance with internal policies and industry regulations. 

This will be sitting in the Equity Quantitative Research team, focusing on quantitative strategies and the optimization of trading for the Equities desks. 

 

The aim here is to develop cutting-edge next generation analytics and processes to transform, automate and improve the trading operations of their Cash, Delta One and Derivatives businesses. They work closely with traders to develop data-driven solutions such as algorithmic strategies (high to low frequency), trading signals, risk models, portfolio optimization, recommendation engines, flow categorization and clustering – and to ultimately combine them into automated trading processes.

 

My client is seeking individuals passionate in areas such as electronic trading, machine learning, reinforcement learning, deep learning, collaborative filtering, recommender systems, optimization, computational statistics, and applied mathematics, with a keen interest to apply these techniques to financial markets and have a transformational impact on the business.

 

Roles and responsibilities:

  • Work closely with trading to build analytics and data-driven processes that automate and optimize trading quantitatively.
  • Contribute from idea generation to production implementation: perform research, design prototype, implement analytics and strategies, support their daily usage and analyse their performance.
  • Leverage on a wide range of modern techniques such as optimization (linear, quadratic, conic…), reinforcement learning, neural networks, time-series forecasting, clustering methods, dimensionality reduction methods (PCA, Kernel methods, factor models…).

Required Skills and Experience:

  • Earned a MS, PhD or equivalent degree program in machine learning, mathematics, statistics, econometrics, financial engineering, computer science, operational research, physics or chemistry.
  • Publications or experience in applied mathematics, statistics, optimization, computer science or data science (machine learning, reinforcement learning, computer vision, NLP…).
  • Exceptional analytical, quantitative and problem-solving skills, as well as the ability to communicate complex research in a clear and precise manner.
  • Entrepreneurial spirit and passion for spreading a culture of change towards data-driven decision making.
  • Strong software design and development skills using Python, C++ or Java.
  • Ability to manipulate and analyze complex, large scale, high-dimensionality data from varying sources (use of TensorFlow and other standard machine learning packages).
  • Experience in finance is helpful, but not required: electronic trading, portfolio analytics (risk modelling, portfolio optimization), trading strategies (high to low frequency: market making, statistical arbitrage, option trading…), derivatives pricing and risk management.
  • Autonomy, excellent communication, strong motivation and interest in electronic trading and equity markets.

 

Londres, Angleterre, Royaume-Uni Londres Angleterre GB