At a Glance
- Tasks: Design and optimise cutting-edge trading strategies in global commodity markets.
- Company: Join a leading global hedge fund with a focus on innovation.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Exciting role with high-impact challenges in mid-frequency trading.
- Why this job: Make a real impact in algorithmic trading and work with top experts.
- Qualifications: Advanced degree in a quantitative field and strong programming skills.
The predicted salary is between 42000 - 84000 £ per year.
A leading global hedge fund is seeking an experienced Quantitative Researcher to join their systematic commodities team in London. This role will focus on mid-frequency trading, with responsibility for the design, implementation, and optimization of advanced trading strategies across global commodity markets.
Responsibilities:
- Design, implement, and optimize mid-frequency algorithmic trading strategies for commodity markets including energy, metals and ags.
- Work alongside the PM with a focus on alpha generation, model implementation, backtesting and portfolio construction.
- Work closely with leading quantitative researchers and engineers to improve existing strategies and identify new trading opportunities.
Qualifications:
- Advanced academic qualifications (Master's/PhD) in a quantitative field, such as Mathematics, Physics, Statistics, Computer Science, or a related discipline.
- Proven experience in generating alpha and developing high-performing strategies within commodity markets.
- Strong background in quantitative trading, with specific expertise in mid-frequency commodity strategies.
- Extensive proficiency in programming languages including Python.
- Deep expertise in machine learning techniques and tools, with a focus on their application in strategy development and optimisation.
This position offers an exceptional opportunity for a seasoned quantitative researcher to make a significant impact within mid-frequency commodity markets. If you are driven by the pursuit of innovation in algorithmic trading and are looking for a challenging, high-impact role, we invite you to apply.
Quantitative Researcher - Commodities in London employer: Algo Capital Group
As a leading global hedge fund based in London, we pride ourselves on fostering a dynamic and innovative work culture that empowers our employees to excel. Our Quantitative Researchers benefit from unparalleled opportunities for professional growth, collaboration with top-tier talent, and the chance to make a significant impact in the fast-paced world of mid-frequency trading. With a focus on cutting-edge technology and a commitment to excellence, we offer a rewarding environment for those passionate about algorithmic trading and quantitative finance.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher - Commodities in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and trading sectors. Attend industry events or webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative research projects, especially those related to commodities. Use platforms like GitHub to share your code and algorithms. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for the interview like it’s a high-stakes trading session. Brush up on your technical knowledge, especially around mid-frequency trading strategies and machine learning applications. Be ready to discuss your past experiences and how they relate to the role.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got exclusive features that can help you stand out. Plus, it shows you’re serious about joining our team. So, get your application in and let’s make some waves in the commodities market together!
We think you need these skills to ace Quantitative Researcher - Commodities in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to highlight your experience in quantitative research and mid-frequency trading. We want to see how your skills align with the role, so don’t hold back on showcasing your achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about algorithmic trading and how your background in commodities makes you a perfect fit for our team. Keep it engaging and relevant!
Showcase Your Technical Skills:Since programming is key for this role, make sure to highlight your proficiency in Python and any machine learning techniques you've used. We love seeing practical examples of how you've applied these skills in your previous work.
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 this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Algo Capital Group
✨Know Your Algorithms
Brush up on your knowledge of algorithmic trading strategies, especially those relevant to commodities. Be prepared to discuss specific models you've implemented and optimised in the past, as well as how you generated alpha from them.
✨Showcase Your Programming Skills
Since proficiency in Python is crucial for this role, make sure you can demonstrate your coding skills. Bring examples of your work or projects that highlight your ability to develop and backtest trading strategies using Python.
✨Understand the Market Dynamics
Familiarise yourself with current trends in the commodity markets, including energy, metals, and agricultural products. Being able to discuss recent market movements and their implications will show your passion and understanding of the field.
✨Prepare for Technical Questions
Expect technical questions related to quantitative methods and machine learning techniques. Review key concepts and be ready to explain how you've applied these tools in your previous roles to optimise trading strategies.
