Saragossa
Job Description
Are you interested in joining one of the premier energy trading organizations in the industry?
This position involves a diverse range of quantitative risk assessment and analytical tasks across a broad spectrum of commodity assets. If you value professional diversity and the ability to make a significant contribution, this role provides both in abundance.
You will remain technically involved—constructing and refining risk frameworks using Python, collaborating intimately with trading desks, risk controllers, and broader data science units to define how the organization evaluates and mitigates exposure. Reporting straight to the Lead Quant Risk, you will enjoy authentic independence and direct interaction with executive stakeholders who prioritize high-level technical expertise.
On a daily basis, you will be upgrading and architecting the company’s primary risk indicators, guaranteeing they are precise, capable of growth, and synchronized with active trading strategies. This is a career path where your specialized depth and grasp of market dynamics will directly impact corporate choices.
Qualified applicants must possess a foundation in the commodities sector, complemented by robust experience in modeling risk indicators (such as VaR, CAR, PFE, and Liquidity at Risk) and advanced Python programming.
Job Data Table
| Category | Details |
| Company Name | Saragossa (on behalf of an Energy Trading Firm) |
| Location | United Kingdom |
| Locality | Remote/Hybrid (Major UK Trading Hubs) |
| Country | United Kingdom |
| City | Not Specified (Likely London or Bristol) |
| Region | Europe |
| Job Type | Full-time |
| Salaries | Competitive Market Rate |
| Experience Level | Intermediate to Senior |
| Travel | Minimal |
| Language | English |
| Benefits | Autonomy, Senior Stakeholder Access, Impactful Projects |
Skills & Competency Table
| Key Skill | Level |
| Python Programming | Expert |
| Risk Metrics (VaR, CAR, PFE, LaR) | Expert |
| Commodities Market Knowledge | Advanced |
| Risk Modeling & Enhancement | Expert |
| Stakeholder Management | Advanced |
| Analytical Problem Solving | Expert |
Salaries Pay Calculator Table
| Annual Salary | Bonus (Est.) | Total Compensation | Notes |
| £85,000 | £25,000 | £110,000 | Baseline for energy trading quants. |
| £115,000 | £50,000 | £165,000 | Mid-range for experienced commodities risk quants. |
| £145,000+ | £80,000+ | £225,000+ | Upper-tier for senior specialists in elite firms. |
Job Summary
This role at a top-tier energy trading firm involves developing and enhancing sophisticated Python-based risk models for various commodity products. You will work alongside traders and senior stakeholders to manage metrics like VaR and PFE, ensuring accurate and scalable risk measurement that directly influences the firm’s trading decisions and strategy.
5 FAQs
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What are the primary risk metrics used? The role focuses on Value at Risk (VaR), Capital at Risk (CAR), Potential Future Exposure (PFE), and Liquidity at Risk (LaR).
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Is Python mandatory? Yes, the role is hands-on and requires building and enhancing core risk models in Python.
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Who does this position report to? You will report directly to the Lead Quant Risk.
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Do I need a commodities background? Yes, a proven background in commodities is a core requirement for this position.
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Is an updated CV required for the initial contact? No, an up-to-date CV is not required to apply or get in touch.
Expert Analysis
In 2026, energy trading risk is increasingly defined by Volatility and Intermittency , especially with the growth of renewables. For a Quant Risk Analyst, moving beyond traditional VaR to Stochastic Liquidity Modeling is crucial. Understanding how physical supply constraints impact PFE during extreme weather events is the next “hard skill” for elite commodities quants.
Location & Logistics Guide
While the specific city is not listed, major UK energy trading hubs include London (Canary Wharf/Mayfair) and Bristol . Most firms in 2026 offer hybrid flexibility, but proximity to the trading floor is essential for the high-collaboration “trader-quant” relationship required in this role. Wikipedia URL:https://en.wikipedia.org/wiki/London
Career Path
A Quant Risk Analyst in Commodities can progress to Lead Quant Risk , Head of Market Risk , or transition into Algorithmic Trading or Structuring . The deep exposure to senior stakeholders and direct impact on trading strategies also provides a path towards Portfolio Management within global energy firms.
To apply for this job please visit uk.linkedin.com.