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Quantitative Researcher - Equity Volatility- Global Hedge Fund

Oxford Knight London, United Kingdom
Posted 3 days ago Permanent £150k // £250k TC

Quantitative Researcher - Equity Volatility- Global Hedge Fund

Oxford Knight London, United Kingdom
Quantitative Researcher - Equity Volatility
Salary: £150k // £250k TC

Experience: 2-6 years

Summary:

Great opportunity for an alpha-strategy-focussed Python Quant Researcher to join one of the world's most prestigious hedge funds.

This is a new specialized team at the firm - Volatility Alpha Development - made up of engineers, quants and data scientists, and you'll work closely with different Portfolio Managers and their trading pods. You will be building a Vol Alpha library for PMs; existing vol PMs on the discretionary side and being part of the build-out and expansion of new systematic vol PMs to help decrease their onboarding time.

The successful Quant Researcher will enjoy facing off to the business and have exceptional communication skills.

Skills and Experience Required:
  • 2-6 years' Python programming experience; some KDB & SQL is useful
  • Substantial experience with equity derivatives modelling, vol surface fitting and backtesting systems
  • Experience with QIS Strategies, Equity Derivatives, Equity vol
  • Some knowledge of developing classic volatility trading strategies, e.g. dispersion, relative value, VIX complex

Rewards and Incentives:
  • Significant salary + bonus and growth
  • Greenfield work / big impact
  • Very collaborative culture, ideas are implemented
  • Work-life balance is highly valued


Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.

Contact
If you feel you're suitable for this role, want to hear about similar positions, or would like help hiring similar developers for your company, please send your CV or get in touch:

Richard Allan
richard.allan@oxfordknight.co.uk
+44 (0) 20 3137 9574
linkedin.com/in/richardallanok/

Job ID  K7Rz8FBfuCpW
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