Quantitative Researcher – Equity Volatility

Oxford Knight; Greater London; On-site; GBP 130,000 - 210,000; Full time

Benefits offered by this job

Salary plus bonus

Collaborative culture

Work-life balance

Job summary

Oxford Knight in London is seeking a Python-focused Quant Researcher to join the new Volatility Alpha Development team. You will work with PMs, quants and data scientists to build a Vol Alpha library and accelerate onboarding for new systematic volatility traders.

The role demands strong communication, hands-on modelling of equity derivatives and vol surfaces, and practical backtesting experience. 2–6 years’ Python experience is expected; KDB/SQL knowledge is a plus.

Qualifications

• 2-6 years of Python programming experience.
• Substantial experience with equity derivatives modelling, vol surface fitting and backtesting systems.
• Experience with QIS Strategies, Equity Derivatives, Equity vol.
• Knowledge of volatility trading strategies (dispersion, relative value, VIX complex).

Responsibilities

• Build a Vol Alpha library for PMs.
• Collaborate with engineers, quants and data scientists to expand systematic volatility strategies.
• Interface with Portfolio Managers and trading pods to improve onboarding time.

Skills

Python

KDB

SQL

Equity derivatives

Volatility modelling

Job description

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
• 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.

Quantitative Researcher – Equity Volatility • London