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- Tasks: Join a team to build and maintain a cutting-edge trading system using quantitative research.
- Company: Dynamic firm focused on innovative finance solutions.
- Benefits: Competitive salary, flexible hours, and opportunities for professional growth.
- Other info: Collaborative environment with exciting projects and career advancement potential.
- Why this job: Make an impact in finance with your analytical skills and programming expertise.
- Qualifications: Masters or PhD in a quantitative field and strong Python programming skills.
The predicted salary is between 60000 - 80000 £ per year.
My client is seeking an experienced quantitative researcher to join a new team focused on building a mid-frequency systematic equities trading system. Build and maintain the quantitative research ecosystem, including data pipelines, backtesting frameworks, and tools for evaluating model performance.
Implement robust logging, monitoring, and diagnostic processes for the trading. Generate, test, and prioritise new research ideas to improve model performance.
Solid understanding of quantitative finance concepts, statistical analysis, and, ideally, practical applications of machine learning. Strong programming expertise in Python and related libraries.
Experience working with large, noisy datasets, including data cleaning and feature engineering. Masters or PhD in a quantitative subject.
Strong organizational skills with the ability to manage multiple projects concurrently. High attention to detail and commitment to code quality.
Quantitative Researcher/Analyst in City of London employer: EC1 Partners
Contact Detail:
EC1 Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher/Analyst in City of London
✨Tip Number 1
Network like a pro! Reach out to professionals in the quantitative finance 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 projects, especially those involving Python and machine learning. This is your chance to demonstrate your expertise and make a lasting impression on potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your quantitative finance concepts and statistical analysis. We recommend practicing coding challenges and mock interviews to boost your confidence and performance.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for talented individuals who are passionate about quantitative research.
We think you need these skills to ace Quantitative Researcher/Analyst in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in quantitative research and programming, especially in Python. We want to see how your skills align with building and maintaining a trading system, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about quantitative finance and how your background makes you a perfect fit for our team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Projects: If you've worked on any relevant projects, whether academic or personal, make sure to mention them. We’re interested in your experience with data pipelines, backtesting frameworks, and model performance evaluation. Real-world examples can really set you apart!
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 the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at EC1 Partners
✨Know Your Quantitative Finance
Brush up on your quantitative finance concepts and statistical analysis. Be ready to discuss how you've applied these in real-world scenarios, especially in relation to building trading systems. This will show your understanding of the field and your ability to contribute effectively.
✨Showcase Your Programming Skills
Since strong programming expertise in Python is crucial, prepare to demonstrate your coding skills. Bring examples of your work with data pipelines or backtesting frameworks. You might even be asked to solve a coding problem on the spot, so practice common algorithms and data manipulation tasks.
✨Prepare for Data Challenges
Expect questions about handling large, noisy datasets. Think of specific instances where you cleaned data or extracted features. Discuss the tools and libraries you used, and how you ensured the quality of your data. This will highlight your practical experience and problem-solving abilities.
✨Organise Your Thoughts
With multiple projects on the go, it's essential to demonstrate your organisational skills. Prepare to talk about how you prioritise tasks and manage your time effectively. Use examples from your past experiences to illustrate your ability to juggle responsibilities while maintaining high attention to detail.