Equity Volatility Quant Researcher: Build Vol Alpha Library

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

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.