Job Overview
Job description
- Location:
- London, New York City, United Kingdom
- Work arrangement:
- On-site
Role Summary
Quantitative Volatility Traders (QVTs) collaborate with developers and researchers to implement Xantium's derivatives trading strategies. Their roles require established Python coding skills, strong mental math, and developed market intuition.
Initial responsibilities include trading system monitoring and improvement; some roles also involve individual trade execution and support. Over time and with guidance from senior team members, all QVTs grow to better understand how the range of Xantium’s volatility strategies are developed and optimized.
We are seeking multiple QVTs for a rapidly growing team. At this time, candidates with derivatives experience in the following underlying asset types are particularly attractive: equities (single name and index), commodities, and fixed income.
Requirements
All applicants should have
- 1-3+ years of fulltime experience trading derivatives or developing options trading systems
- Bachelor’s degree (or higher) in hard sciences (e.g., mathematics, computer science, physics, engineering, etc.)
- Strong Python coding skills
Compensation: Quantitative Volatility Traders in New York can expect to earn $150,000 to $225,000+ base. Total compensation for all Quantitative Volatility Traders also includes a large annual bonus which is guaranteed in year one and based on employee and firm performance thereafter.
- Role:
- Quantitative Volatility Trader
Company profile
Xantium
xantium.comXantium is a global multi-strategy investment firm that integrates quantitative research with human expertise to trade global markets. At Xantium, quantitative researchers, developers, fundamental analysts and traders work together to create strategies designed to perform across market cycles, building technology enhanced by human insight. The firm describes its edge as earned ex ante, grounded in priors and refined through evidence, and emphasises global presence, market breadth and scale.