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- Tasks: Drive alpha and signal generation in a collaborative equities stat arb team.
- Company: High-performing, research-led team based in London with strong engineering support.
- Benefits: Visa sponsorship available, real ownership of projects, and visible impact on PnL.
- Other info: On-site role in London with a high-accountability team environment.
- Why this job: Join a rare opportunity for genuine signal ownership and career growth.
- Qualifications: 2-5 years in systematic equity research, strong programming skills, and statistical intuition.
The predicted salary is between 36000 - 60000 £ per year.
A high-performing, research-led, collaborative equities stat arb team in London is hiring a Quant Researcher to drive alpha and signal generation. This is a rare chance to join a lean pod where researchers have real ownership, strong engineering support around them, and a clear mandate across cash equities.
Scope
- Research, design, and validate alpha signals for cash equities stat arb strategies
- Build robust feature sets from market, fundamental, and alternative datasets
- Run disciplined backtesting and statistical validation to avoid overfitting
- Translate research into production-ready signals in collaboration with engineering
- Monitor live performance and iterate on signals as market regimes shift
- Contribute to idea generation and the team’s evolving research framework
Ideal profile
- 2 to 5 years of experience in systematic equity research
- Strong statistical intuition and a rigorous research process (hypothesis, testing, validation)
- Solid programming skills (Python required; familiarity with research-to-production workflows is a plus)
- Experience working with equities data and market microstructure awareness preferred
- Candidates from prop trading environments are interesting, but top long-only / fundamental researchers with a systematic mindset are also of interest
- Comfort working in a small, high-accountability team where your work has visible impact
Nice to have
- Single-stock research exposure with a clear, testable signal mindset
- Experience with factor research, statistical arbitrage, or systematic equities strategies
- Familiarity with portfolio construction concepts and risk-aware signal development
Logistics
- London-based role, on-site
- No remote / overseas-based working
- Hiring timeline: next 1 to 2 months
If you’re a mid-level researcher who wants genuine signal ownership and a direct line between your work and PnL, this is the kind of seat that doesn’t come up often.
Quant Researcher - Collaborative Cash Equities Team - daily to monthly holding period employer: J K Barnes
Contact Detail:
J K Barnes Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Researcher - Collaborative Cash Equities Team - daily to monthly holding period
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at firms you're interested in. A friendly chat can sometimes lead to opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your research projects, backtesting results, and any alpha signals you've developed. This will give potential employers a taste of what you can bring to their team.
✨Tip Number 3
Prepare for interviews by brushing up on your statistical intuition and programming skills. Be ready to discuss your research process and how you've validated your findings. Confidence in your expertise can really set you apart!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Quant Researcher - Collaborative Cash Equities Team - daily to monthly holding period
Some tips for your application 🫡
Show Your Research Skills: Make sure to highlight your experience in systematic equity research. We want to see your strong statistical intuition and how you've applied a rigorous research process in your previous roles.
Demonstrate Programming Proficiency: Since Python is a must-have, don’t forget to showcase your programming skills. Share examples of how you've used Python in your research-to-production workflows to give us a clear picture of your technical abilities.
Tailor Your Application: Take the time to tailor your application to our specific needs. Mention your familiarity with equities data and market microstructure, as well as any relevant experience in statistical arbitrage or factor research.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and get you into our hiring pipeline quickly!
How to prepare for a job interview at J K Barnes
✨Know Your Stats
Brush up on your statistical intuition and research processes. Be ready to discuss your hypothesis testing and validation methods in detail, as this role demands a rigorous approach to research.
✨Showcase Your Coding Skills
Since Python is a must-have, make sure you can demonstrate your programming skills. Prepare to talk about any projects where you've translated research into production-ready signals, highlighting your familiarity with research-to-production workflows.
✨Understand the Market
Familiarise yourself with equities data and market microstructure. Be prepared to discuss how you've used this knowledge in past roles, especially in relation to alpha signal generation and systematic strategies.
✨Emphasise Collaboration
This role is all about teamwork, so be ready to share examples of how you've worked in small, high-accountability teams. Highlight instances where your contributions had a visible impact on the team's success and idea generation.