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- Tasks: Build optimisers and analytical tools for trade analysis using Python.
- Company: Leading investment firm with a focus on innovation and collaboration.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Why this job: Collaborate with top-tier PMs and leverage AI/ML techniques to drive investment success.
- Qualifications: Strong skills in Python and equity market analysis, especially in long/short strategies.
- Other info: Join a talented team dedicated to generating alpha through innovative approaches.
The predicted salary is between 43200 - 72000 £ per year.
A leading investment firm is seeking an experienced Quant Researcher to work closely with top-tier PMs in London. The position requires strong skills in Python and equity market analysis, particularly within long/short strategies.
The role focuses on building optimisers and analytical tools used for trade analysis, contributing to innovative projects that integrate AI/ML techniques. This unique opportunity entails collaboration within a highly talented team dedicated to generating alpha through a fundamental and quantitative approach.
L/S Equity Quant Researcher — Direct PM Collaboration employer: Octavius Finance
Contact Detail:
Octavius Finance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land L/S Equity Quant Researcher — Direct PM Collaboration
✨Tip Number 1
Network like a pro! Reach out to professionals in the investment and quant research space on LinkedIn. A friendly message can go a long way, and who knows, they might just point you towards your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects and equity market analyses. This is your chance to demonstrate your expertise and creativity, making you stand out to potential employers.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of long/short strategies and be ready to discuss how you've used AI/ML techniques in your work. Confidence and preparation are key to impressing those top-tier PMs.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can give you an edge. Let’s get you one step closer to landing that Quant Researcher role!
We think you need these skills to ace L/S Equity Quant Researcher — Direct PM Collaboration
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python expertise and any experience you have with equity market analysis. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specifics of the job description. Mention your experience with long/short strategies and any relevant projects that showcase your analytical abilities.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your key achievements and experiences stand out without unnecessary fluff.
Apply Through Our Website: We encourage you 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 Octavius Finance
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be prepared to discuss specific libraries and frameworks you've used, especially those relevant to quantitative analysis. Practising coding problems can also help you demonstrate your technical prowess.
✨Understand Long/Short Strategies
Familiarise yourself with long/short equity strategies and be ready to discuss how they work. Think about past experiences where you've applied these strategies or how you've contributed to similar projects. This will show your potential employer that you have a solid grasp of the role's requirements.
✨Showcase Your Analytical Tools
Prepare to talk about any optimisers or analytical tools you've built in the past. Highlight how these tools have improved trade analysis or decision-making processes. If possible, bring examples or case studies to illustrate your contributions and impact.
✨Emphasise Collaboration Skills
Since this role involves working closely with PMs, it's crucial to demonstrate your ability to collaborate effectively. Share examples of how you've worked in teams, particularly in high-pressure environments, and how you’ve communicated complex quantitative concepts to non-technical stakeholders.
