At a Glance
- Tasks: Develop and optimise trading strategies in commodities markets from start to finish.
- Company: Durlston Partners, a leader in quantitative research and trading.
- Benefits: Competitive salary, bonus structure, and opportunities for profit sharing.
- Other info: Collaborative environment with ownership of projects and career advancement potential.
- Why this job: Join a dynamic team and make an impact in the commodities trading world.
- Qualifications: Master's or PhD in a quantitative field with Python and machine learning skills.
The predicted salary is between 60000 - 80000 £ per year.
Durlston Partners is seeking a Commodities Quantitative Researcher to develop and optimize systematic trading strategies across various commodities markets. This role requires ownership of projects from hypothesis to production deployment, working closely with traders and engineers.
Ideal candidates will hold a master's or PhD in a quantitative field, with at least 2 years of related research experience. Skills in Python and familiarity with machine learning methods are essential. The position offers a competitive salary and bonus structure aligned with profits.
Quantitative Commodities Researcher – Alpha Signals employer: DURLSTON PARTNERS
Durlston Partners is an exceptional employer, offering a dynamic work environment where innovation thrives and employees are empowered to take ownership of their projects. With a strong focus on professional development, competitive compensation, and a collaborative culture that bridges the gap between research and trading, this role in the vibrant commodities market provides unique opportunities for growth and impact.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Commodities Researcher – Alpha Signals
✨Tip Number 1
Network like a pro! Reach out to professionals in the commodities trading space on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative research projects, especially those involving Python and machine learning. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practising common quantitative interview questions and even doing mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Quantitative Commodities Researcher – Alpha Signals
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your Python skills and any experience with machine learning in your application. We want to see how you can bring those skills to the table for developing trading strategies!
Be Project-Focused:Since this role involves ownership of projects, share examples of past research or projects you've led from start to finish. We love seeing candidates who can take initiative and drive results!
Tailor Your Application:Don’t just send a generic CV! Tailor your application to reflect the specific requirements of the Quantitative Commodities Researcher role. We appreciate when candidates take the time to align their experiences with what we’re looking for.
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 don’t miss out on any important updates during the process!
How to prepare for a job interview at DURLSTON PARTNERS
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative skills, especially in areas related to commodities trading. Be ready to discuss your previous research projects and how they relate to systematic trading strategies. We recommend preparing specific examples that showcase your analytical thinking and problem-solving abilities.
✨Show Off Your Python Skills
Since Python is a key requirement for this role, practice coding problems or projects that demonstrate your proficiency. We suggest having a couple of mini-projects ready to discuss during the interview, highlighting how you've used Python in your past work, especially in relation to machine learning methods.
✨Understand the Market
Familiarise yourself with current trends in the commodities market. We advise reading up on recent news and reports, so you can engage in informed discussions about market dynamics and how they might impact trading strategies. This shows your genuine interest and understanding of the field.
✨Prepare for Collaboration Questions
This role involves working closely with traders and engineers, so be prepared to discuss your teamwork experiences. We suggest thinking of examples where you've successfully collaborated on projects, particularly those that required cross-functional communication. Highlighting your ability to work well with others will set you apart.
