Quant Development Lead

JR United Kingdom; London; On-site; GBP 70,000 - 110,000; Full time

Job summary

An innovative commodities trading firm is on the lookout for a Lead Quant Developer to join their dynamic team in London. This role focuses on Risk and PnL, where you'll leverage your expertise in risk modelling and Python programming. Collaborating closely with traders and risk managers, you will enhance analytics and develop robust Historical VaR models for various products. If you're passionate about quantitative finance and eager to make a significant impact in a rapidly growing firm, this opportunity is perfect for you.

Qualifications

• Strong understanding of risk modelling, particularly Historical VaR.
• Proficiency in Python and ability to work with existing codebases.

Responsibilities

• Develop and enhance Historical VaR models for linear and options products.
• Maintain and improve risk reporting tools to align with business limits.

Skills

Python

Risk Modelling

VaR Models

Quantitative Analysis

Troubleshooting

Job description

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One of our clients is a growing commodities trading firm, and they are seeking a Lead Quant Developer in London to focus on Risk and PnL. You would be working in and with the front office and wider technology team, as well as risk and quant teams.

Key Responsibilities:

• Work extensively with VaR (Value at Risk) models.
• Develop and enhance Historical VaR models for linear and options products.
• Maintain and improve risk reporting tools to align with business limits.
• Troubleshoot and resolve risk calculation and reporting issues.
• Own the full modelling process (all modelling sits within the development group).
• Work closely with traders and risk managers to improve analytics.

Key Requirements:

• Strong understanding of risk modelling, particularly Historical VaR.
• Proficiency in Python (other language experience welcome, but Python is essential).
• Ability to work with existing codebases and apply models to trading scenarios.
• Business-savvy—must understand risk limits, reporting, and troubleshooting.
• Excellent knowledge within the commodities trading space, particularly with linear and options products. Physicals is a plus, but not necessary.
• Good quant exposure and understanding (there is no need for heavy Monte Carlo modelling, but someone with a practical and applied understanding of quantitative concepts).