VP – Risk Analytics – Prop Trading
Specialisms: Quant Jobs
1. London
2. £ market leading total comp
3. Job type: Permanent
4. Sector: Banking, Financial Services
5. Job reference: SN43462
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I am looking for an experienced and technically skilled Risk Analytics Manager to join a growing financial services group operating across trading, investment advisory, and market making. This is a fantastic opportunity for someone who thrives on building tools, solving complex problems, and turning data into meaningful insights that drive critical decisions.
As part of a high-performance risk team, you’ll lead the development and enhancement of dashboards, data pipelines, and models that power our risk analytics infrastructure. Your work will directly influence how risk is understood, monitored, and managed across a global, multi-asset platform.
The Role
You’ll be responsible for the tools and systems used to measure and report risk across the business. This includes developing analytics, improving data integrity, and partnering closely with teams across trading, technology, and operations. The role is hands-on, highly visible, and ideal for someone who can combine financial knowledge with strong programming skills.
You’ll design and maintain dashboards for real-time and historical risk monitoring, enhance key risk measures such as VaR, P&L attribution, and stress scenarios, and develop robust data pipelines to support risk modelling and reporting. You’ll work closely with cross-functional teams to align analytics with business objectives while ensuring data quality and consistency across systems. Clear documentation of methodologies and assumptions is also essential.
The Person
The ideal candidate will have significant experience working at VP level in risk analytics, risk modelling or a similar quantitative role in financial services with a strong preference for hedge funds or prop trading firms. Strong skills in Python and SQL are required; experience with Django and JavaScript is a plus. A solid understanding of trading strategies, financial instruments, and risk metrics is essential, along with familiarity with tools like Bloomberg or Imagine. A bachelor’s degree in a quantitative field is required, and a master’s degree in a data-driven discipline is preferred. Strong communication skills are key.
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Scott Nye – Quant Risk
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