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- Tasks: Develop and enhance risk models in Python while collaborating with traders and risk managers.
- Company: Join a leading energy trading firm known for its success and innovation.
- Benefits: Gain autonomy, access to senior stakeholders, and work on impactful projects.
- Why this job: Make a real difference in how commodities risk is measured and managed.
- Qualifications: Experience in commodities and strong skills in modelling and Python required.
- Other info: No up-to-date CV needed; apply directly for this exciting opportunity.
The predicted salary is between 36000 - 60000 £ per year.
Want to work at one of the most successful energy trading firms? Here you’ll take on a broad mix of quantitative risk and analytics work across a wide range of commodities products. If you enjoy variety and real impact, this is the kind of role that offers both. You’ll stay hands-on - building and enhancing risk models in Python, working closely with traders, risk managers and the wider analytics teams, and shaping how the firm measures and manages risk. Reporting directly to the Lead Quant Risk, you’ll have genuine autonomy and access to senior stakeholders who value strong technical judgement.
Day to day, you’ll be improving and developing the firm’s core risk metrics, ensuring they’re accurate, scalable and aligned with how the business trades. It’s a role where your technical depth and market understanding will genuinely influence decision-making.
You’ll need a background in commodities, alongside strong modelling and risk metrics (VAR, CAR, PFE, Liquidity at Risk) and Python skills.
If you want to join a firm pushing the future of commodities, apply or get in touch directly at megan@saragossa.io. No up-to-date CV required.
Responsibilities:- Hands-on development and enhancement of risk models in Python
- Collaborating with traders, risk managers and the wider analytics teams
- Shaping how the firm measures and manages risk
- Improve and develop the firm’s core risk metrics, ensuring they’re accurate, scalable and aligned with how the business trades
- Reporting to the Lead Quant Risk with autonomy and access to senior stakeholders
- Background in commodities
- Strong modelling and risk metrics experience (VAR, CAR, PFE, Liquidity at Risk)
- Python skills
Quant Risk Analyst - Commodities - Saragossa employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Risk Analyst - Commodities - Saragossa
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those already working at Saragossa. A friendly chat can open doors and give you insights that might just set you apart from the crowd.
✨Tip Number 2
Show off your skills! If you’ve got some cool Python projects or risk models up your sleeve, don’t hesitate to share them. A portfolio can really make you stand out and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of commodities and risk metrics. Be ready to discuss how you would improve risk models and metrics, as this shows you’re not just a fit but a proactive thinker.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the team at Saragossa. Don’t miss out!
We think you need these skills to ace Quant Risk Analyst - Commodities - Saragossa
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that are relevant to the Quant Risk Analyst role. Highlight your background in commodities and any specific modelling or risk metrics experience you have, like VAR or PFE.
Show Off Your Python Skills: Since you'll be building and enhancing risk models in Python, it's crucial to showcase your programming skills. Include any projects or experiences where you've used Python for quantitative analysis or risk management.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experiences and how they relate to the responsibilities of the role. We want to see your impact and how you can contribute to our team!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Jobster
✨Know Your Commodities
Make sure you brush up on your knowledge of commodities and the specific market dynamics that affect them. Being able to discuss recent trends or challenges in the commodities sector will show your genuine interest and understanding of the field.
✨Showcase Your Python Skills
Prepare to discuss your experience with Python, especially in relation to building risk models. Bring examples of projects you've worked on or problems you've solved using Python, as this will demonstrate your technical capabilities effectively.
✨Understand Risk Metrics
Familiarise yourself with key risk metrics like VAR, CAR, PFE, and Liquidity at Risk. Be ready to explain how these metrics are calculated and their importance in risk management, as this knowledge will be crucial for the role.
✨Engage with Stakeholders
Since you'll be working closely with traders and risk managers, think about how you can communicate complex quantitative concepts clearly. Prepare to discuss how you would collaborate with different teams and influence decision-making through your analysis.
