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- Tasks: Develop pricing and volatility models for trading and risk management.
- Company: Leading Global Investment Bank in Greater London with a high-performing team.
- Benefits: Full-time role with significant responsibilities and collaborative environment.
- Why this job: Join a dynamic team and make an impact in the commodities market.
- Qualifications: Strong quantitative skills, proficiency in C++ and Python, advanced degree required.
- Other info: Exciting opportunity for career growth in a fast-paced financial sector.
The predicted salary is between 42000 - 84000 £ per year.
A leading Global Investment Bank in Greater London is seeking a Quantitative Analyst to join a high-performing Commodities team. This mid-senior level role focuses on developing pricing and volatility models that impact trading and risk management.
Ideal candidates will have:
- Strong quantitative skills
- Proficiency in C++ and Python
- An advanced degree in a relevant field
The position offers a full-time employment opportunity with significant responsibilities that require strong analytical prowess and collaboration with various teams.
Quantitative Analyst, Commodities Derivatives & Models in London employer: JCW Group
Contact Detail:
JCW Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst, Commodities Derivatives & Models in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the commodities and finance sectors on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative models and coding projects in C++ and Python. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your analytical skills and be ready to discuss your approach to developing pricing and volatility models. Practice common interview questions related to risk management.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Quantitative Analyst, Commodities Derivatives & Models in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your quantitative skills and programming prowess in C++ and Python. We want to see how your background aligns with the role, so don’t hold back on showcasing your relevant experience!
Tailor Your Application: Customise your CV and cover letter to reflect the specifics of the job description. Mention your experience with pricing and volatility models, as this will show us you understand what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and fit for the role.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at JCW Group
✨Brush Up on Your Quant Skills
Make sure you’re well-versed in quantitative analysis and the specific models used in commodities trading. Review key concepts and be ready to discuss how you've applied them in past roles or projects.
✨Show Off Your Coding Skills
Since proficiency in C++ and Python is crucial, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges related to financial modelling and data analysis.
✨Know the Market
Stay updated on current trends in the commodities market. Be prepared to discuss how these trends could impact pricing and risk management, showcasing your understanding of the industry and its dynamics.
✨Collaboration is Key
This role involves working with various teams, so highlight your teamwork experience. Share examples of how you’ve successfully collaborated on projects, especially those that required cross-functional communication and problem-solving.
