Equity Derivatives Quantitative Research – Associate / VP

  • Competitive Market Rate
  • London, England, United Kingdom
  • Permanent, Full time
  • Anson McCade
  • 20 Sep 16

Work in close collaboration with Flow & Exotics Equity Derivatives traders to quantitatively optimize trading operations. This involves working on risk management (Delta and Vega hedging…), derivatives portfolio optimization, systematic relative value analysis, trading signals & strategies and improving the efficiency of execution… In practice: perform research, build models, tools and processes, support the trading desk on these fields.

Equity Derivatives Quantitative Research – Associate / VP

London based

Work in close collaboration with Flow & Exotics Equity Derivatives traders to quantitatively optimize trading operations. This involves working on risk management (Delta and Vega hedging…), derivatives portfolio optimization, systematic relative value analysis, trading signals & strategies and improving the efficiency of execution… In practice: perform research, build models, tools and processes, support the trading desk on these fields.

Additionally, work on the listed option execution algorithms, which are written in C++ and trade autonomously. Perform tick-by-tick simulation of algorithms using the C++ framework. Perform post-trade analysis with Python to optimize performance. Implement new algorithms or improve existing ones, working closely with the Flow & Exotics traders to define requirements.

My client are looking for an experienced quant (VP / Associate) for this versatile role which mixes classical derivatives quant skills with statistical modeling and optimization. Autonomy, good communication, strong motivation and curiosity towards derivatives trading and equity markets are critical for this role.

Requirements:

  • Derivatives: excellent knowledge of pricing and risk management theory (Black & Scholes…), vanilla options and volatility products (variance swaps, VIX futures and options, stochastic volatility models …)
  • Statistical modeling & optimization: standard techniques, machine learning. Linear, convex & conic optimization…
  • Strong coding background: ability to work with large amounts of data and comfortable with technology, proficient in Python and relevant quantitative packages (numpy, pandas, scikit…), good knowledge of C++ and linux/unix.
  • Experience with electronic markets would be beneficial.