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- Tasks: Analyse trading behaviour and uncover market insights using large-scale data.
- Company: G-Research, a leader in quantitative finance with a focus on innovation.
- Benefits: Competitive pay, annual bonus, 35 days leave, and free lunch.
- Why this job: Join a dynamic team to drive impactful changes in the financial world.
- Qualifications: Experience in quantitative analysis, strong coding skills in Python or C#.
- Other info: Enjoy a flexible work environment with great career growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Join to apply for the Quantitative Analyst role at G-Research. We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. We build smart strategies that win over time. We unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we are building a world-class platform to amplify our teams' most powerful ideas. Join a research team where curiosity meets scale. You will investigate foundational questions, uncover market insights and push the boundaries of what is possible - all with the support of near-limitless compute and world-class peers.
With access to large scale data and compute, our Quantitative Analysts review and refine client trading behaviour to enable new opportunities and maximise performance. You will work closely with other Research teams, as well as those in Engineering and Front Office, to make improvements, respond to external changes and identify new opportunities across a complex, global client trading platform. Attention to detail and communication is key. You will perform post-trade analysis in Python using large scale data and compute, implement performant production C# code in the trading platform and monitor your changes in the real-world. Your work will range between medium term strategic projects and short-term urgent tasks - prioritisation skills and pragmatic decision making to deliver commercial value are necessary.
Qualifications:
- Demonstrable experience in a quantitative role working at pace with an excellent performance track record
- An appreciation of market microstructure and algorithmic order placement behaviour
- Strong coding skills, ideally Python and C#, but other languages are welcome
- The ability to question the status quo and drive improvement and changes
- A strong interest in finance and the motivation to rapidly learn and deliver
Benefits:
- Highly competitive compensation plus annual discretionary bonus
- Lunch provided (via Just Eat for Business) and dedicated barista bar
- 35 days' annual leave
- 9% company pension contributions
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- Monthly company events
Seniority level: Associate
Employment type: Full-time
Job function: Analyst and Research
Industries: Financial Services and Capital Markets
Quantitative Analyst in London employer: G-Research
Contact Detail:
G-Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at G-Research on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your Python and C# skills. Be ready to discuss your past projects and how you've tackled complex problems in quantitative finance. Show them you’re not just a coder, but a problem-solver!
✨Tip Number 3
Don’t forget to showcase your curiosity! During interviews, ask insightful questions about their research processes and how they tackle market challenges. This shows you’re genuinely interested and ready to contribute.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, you’ll have access to exclusive resources that can help you stand out in the competitive field of quantitative analysis.
We think you need these skills to ace Quantitative Analyst in London
Some tips for your application 🫡
Show Your Quantitative Skills: Make sure to highlight your experience in quantitative roles. We want to see how you've tackled complex problems and delivered results, so don’t hold back on showcasing your achievements!
Tailor Your Application: Take a moment to customise your CV and cover letter for the Quantitative Analyst role. We love seeing candidates who understand our mission and can connect their skills to what we do at G-Research.
Demonstrate Your Coding Proficiency: Since coding is key for this role, be sure to mention your experience with Python and C#. If you’ve worked with other languages, throw those in too! We appreciate versatility and a willingness to learn.
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’s super easy!
How to prepare for a job interview at G-Research
✨Know Your Numbers
Brush up on your quantitative skills and be ready to discuss specific examples of your work. G-Research values a strong performance track record, so prepare to showcase your achievements in previous roles, especially those involving data analysis and trading behaviour.
✨Master the Tech Stack
Since coding is a big part of the role, make sure you're comfortable with Python and C#. Be prepared to answer technical questions or even solve coding problems during the interview. Practising coding challenges can help you feel more confident.
✨Show Your Curiosity
G-Research is all about pushing boundaries and exploring new ideas. During the interview, demonstrate your curiosity by asking insightful questions about their projects and methodologies. This shows that you're not just interested in the role, but also in contributing to their innovative environment.
✨Prioritisation is Key
With a mix of medium-term projects and urgent tasks, it's crucial to show that you can prioritise effectively. Prepare examples of how you've managed competing deadlines in the past, and be ready to discuss your decision-making process when it comes to delivering commercial value.
