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- Tasks: Research and develop innovative trading strategies in commodities futures markets.
- Company: Join a top-tier hedge fund with a successful systematic trading team.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborate with a fast-paced team and contribute to cutting-edge trading strategies.
- Why this job: Make an impact in algorithmic trading while working with advanced quantitative techniques.
- Qualifications: 2-5 years of experience in quantitative research and strong Python programming skills.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Quantitative Researcher to join a successful systematic trading team at a tier‑1 hedge fund in their London or Dubai office. The team trades mid‑frequency systematic commodities futures strategies, with holding periods ranging from intraday to several days. You will leverage advanced quantitative techniques to enhance commodities futures strategies and drive improvements in algorithmic trading performance. Following several very successful years, the team is continuing to scale and is seeking a quantitative researcher who can contribute innovative ideas and work closely with the Portfolio Manager to support research, design, and implementation.
The ideal candidate will have 2-5 years of experience as a quantitative researcher in the systematic commodities or futures space and be a strong Python programmer with a solid grounding in quantitative analysis.
Key Responsibilities- Research and develop systematic trading strategies focused on the commodities futures markets.
- Identify and evaluate new alpha signals.
- Perform backtesting, validation, and performance analysis of strategies.
- Analyse market behaviour and relevant macroeconomic drivers.
- Contribute to ongoing improvements in research tools, data pipelines, and modelling frameworks.
- 2-5 years of experience in quantitative research within commodities and/or futures trading.
- Strong programming skills in Python.
- Solid understanding of statistics, quantitative modelling, and time‑series analysis.
- Experience working with large datasets and backtesting frameworks.
- Strong analytical mindset, attention to detail, and a systematic approach to research.
- Ability to work independently while collaborating effectively within a fast‑paced trading team.
- Advanced degree (Master's/PhD) in a quantitative field such as Mathematics, Statistics, Computer Science, or a related discipline.
- Strong programming skills in C++.
- Knowledge of global macroeconomic factors and their impact on financial markets.
Quantitative Researcher - Commodities Futures in London employer: Selby Jennings
Contact Detail:
Selby Jennings Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher - Commodities Futures in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to quantitative research and commodities trading. You never know who might have a lead on your dream job!
✨Show Off Your Skills
Create a portfolio showcasing your quantitative research projects and Python programming skills. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can bring to the table!
✨Ace the Interview
Prepare for technical interviews by brushing up on your quantitative analysis and backtesting frameworks. Practice explaining your thought process clearly and concisely. Remember, they want to see how you think, not just what you know!
✨Apply Through Us!
Don’t forget to check out our website for openings at top-tier hedge funds. Applying through us can give you an edge, as we often have insider knowledge about what employers are really looking for!
We think you need these skills to ace Quantitative Researcher - Commodities Futures in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience in quantitative research, especially in commodities and futures. We want to see how your skills align with the role, so don’t be shy about showcasing your Python programming prowess and any relevant projects you've worked on.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about systematic trading and how your background makes you a perfect fit for our team. We love seeing innovative ideas, so feel free to share any unique insights you have about the commodities market.
Showcase Your Analytical Skills: In your application, make sure to highlight your analytical mindset and attention to detail. We’re looking for someone who can dive deep into data and come up with actionable insights, so include examples of how you've done this in past roles or projects.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Selby Jennings
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative analysis skills and be ready to discuss your experience with statistical modelling and time-series analysis. Be prepared to explain how you've applied these techniques in past roles, especially in commodities or futures trading.
✨Show Off Your Python Skills
Since strong programming skills in Python are a must, come armed with examples of projects or strategies you've developed using Python. You might even want to prepare a small coding challenge or two to demonstrate your proficiency during the interview.
✨Understand the Market
Familiarise yourself with current trends in the commodities futures market and be ready to discuss macroeconomic factors that influence trading strategies. Showing that you can connect your quantitative skills with real-world market behaviour will impress the interviewers.
✨Collaborate and Communicate
Even though you'll be working independently, it's crucial to show that you can collaborate effectively within a team. Prepare examples of how you've worked with others in fast-paced environments and how you communicate complex ideas clearly to non-technical stakeholders.