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- Tasks: Design and build high-performance applications for commodities trading, focusing on LNG.
- Company: Dynamic energy firm in London with a focus on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a small team to tackle complex trading challenges and make a real impact.
- Qualifications: Degree in a quantitative field and strong programming skills in Python required.
- Other info: Exciting opportunity to work with cutting-edge technologies and develop your career.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a highly skilled and motivated Quantitative Engineer with a focus on Commodities Trading, and ideally LNG. You will be part of a small but growing team where you will work directly with the business on complex technology trading problems. You will collaborate with Analysts, Traders and Software Engineers cross-functionally.
KEY RESPONSIBILITIES
- Work closely with the trading desks (traders, originators, structurers and analysts) to acquire in-depth business knowledge, identify their challenges, and capture specific needs.
- Design and build scalable, high-performance end-to-end applications and implement quantitative models for structuring deal evaluations, trading, risk management and portfolio optimization.
- Calibrate models to market data, including curves, volatilities, and correlations; perform back-testing, stress testing, and monitor model performance.
- Implement robust applications to replace Excel-based processes where applicable, to enhance reliability, reduce operational complexity and minimise operational risk.
- Contribute to the development of the shared quantitative platform designed to support all trading desks.
- Utilise cutting-edge technologies, such as cloud computing, to drive improvements in efficiency and productivity for the trading desk.
- Take ownership of the delivery and maintenance of high-quality code and provide prompt, effective support to resolve issues as they arise.
Qualifications and Requirements:
- Degree educated in either Computer Science, Mathematics, Statistics, Financial Engineering, or a related quantitative field.
- Strong programming skills and advanced proficiency in Python.
- Strong understanding of probability theory and derivative option pricing.
- Experience with front-end frameworks such as Angular or React, and understanding of database management, including SQL or NoSQL systems.
- Experience with Continuous Integration/Continuous Deployment (CI/CD) practices and cloud computing platforms.
- Intellectual curiosity and willingness to learn new models and physical commodity markets.
- Excellent problem-solving skills and a strong attention to detail.
- Strong stakeholder communication skills.
- Prior experience in commodities trading is beneficial but not required.
Quantitative Developer - Energy - London employer: Options Group
Contact Detail:
Options Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer - Energy - London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. The more you engage, the better your chances of landing that Quantitative Developer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to commodities trading or quantitative models. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your programming skills, especially in Python. Practice coding challenges and be ready to discuss your thought process when solving problems.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Make sure your application stands out by tailoring it to the specific role and highlighting your relevant experience.
We think you need these skills to ace Quantitative Developer - Energy - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Developer role. Highlight your programming skills, especially in Python, and any relevant experience in commodities trading or quantitative analysis. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your skills can help us tackle complex trading problems. Be specific about your experiences and how they relate to the responsibilities listed in the job description.
Showcase Your Projects: If you've worked on any relevant projects, whether academic or personal, make sure to include them. We love seeing practical applications of your skills, especially if they involve quantitative models or technology solutions that enhance trading processes.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Options Group
✨Know Your Quantitative Stuff
Brush up on your knowledge of probability theory, derivative option pricing, and any relevant quantitative models. Be ready to discuss how you've applied these concepts in real-world scenarios, especially in commodities trading.
✨Show Off Your Coding Skills
Make sure you can demonstrate your programming prowess, particularly in Python. Prepare to talk about specific projects where you've built scalable applications or implemented CI/CD practices, as this will show your technical depth.
✨Understand the Business Side
Familiarise yourself with the trading desk's operations and challenges. Think about how your skills can help solve their problems, and be prepared to discuss how you would approach working closely with traders and analysts.
✨Communicate Clearly
Strong stakeholder communication skills are key. Practice explaining complex technical concepts in simple terms, as you'll need to collaborate with non-technical team members. This will demonstrate your ability to bridge the gap between tech and trading.