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- Tasks: Drive alpha and signal generation in a collaborative equities stat arb team.
- Company: Leading financial research firm with a focus on innovation.
- Benefits: Ownership of signals, high accountability, and direct impact on PnL.
- Other info: Join a team that values collaboration and offers growth opportunities.
- Why this job: Make a real difference in a dynamic environment with your statistical and programming skills.
- Qualifications: 5-15 years in systematic equity research, strong stats, and Python programming.
The predicted salary is between 60000 - 80000 £ per year.
A leading financial research firm is seeking a Quant Researcher in London. This role involves driving alpha and signal generation within a collaborative equities stat arb team. Ideal candidates should have 5-15 years of experience in systematic equity research, strong statistical skills, and solid programming capabilities in Python. The position offers genuine ownership of signals and a chance to contribute directly to PnL in a high-accountability environment.
Quant Researcher, Equities Stat Arb — London (On-site) employer: J K Barnes
Contact Detail:
J K Barnes Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Researcher, Equities Stat Arb — London (On-site)
✨Tip Number 1
Network like a pro! Reach out to current or former employees in the equities stat arb space. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio of your past projects or research that highlights your statistical prowess and Python programming. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on common quant interview questions and coding challenges. We can even do mock interviews with friends to get comfortable with the process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have insider tips on what the hiring team is looking for.
We think you need these skills to ace Quant Researcher, Equities Stat Arb — London (On-site)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your statistical skills and programming capabilities in Python. We want to see how your experience aligns with the role, so don’t hold back on showcasing your best work!
Tailor Your Application: Customise your CV and cover letter to reflect the specifics of the Quant Researcher position. Mention your experience in systematic equity research and how it relates to driving alpha and signal generation.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and ensure your key achievements stand out. This helps us quickly see why you’d be a great fit!
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 in our collaborative team.
How to prepare for a job interview at J K Barnes
✨Know Your Stats
Brush up on your statistical skills before the interview. Be ready to discuss key concepts and how you've applied them in your previous roles. This will show that you have a solid foundation for driving alpha and signal generation.
✨Showcase Your Python Skills
Prepare to demonstrate your programming capabilities in Python. You might be asked to solve a problem or explain your coding process, so having examples of your work or projects handy can really set you apart.
✨Understand the Firm's Focus
Research the firm’s approach to equities stat arb and be prepared to discuss how your experience aligns with their goals. Showing that you understand their strategies and challenges will highlight your genuine interest in the role.
✨Emphasise Collaboration
Since this role involves working within a collaborative team, be ready to share examples of how you've successfully worked with others in the past. Highlighting your teamwork skills will demonstrate that you can thrive in a high-accountability environment.