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- Tasks: Lead projects in electronic trading, develop algorithms, and enhance trading models.
- Company: Join a top-tier investment bank with a stellar Electronic Execution team.
- Benefits: Enjoy competitive pay, mentorship opportunities, and a dynamic work environment.
- Why this job: Shape the future of trading while collaborating globally in a cutting-edge field.
- Qualifications: Master's or PhD in a quantitative discipline; strong coding skills in C++, R, and Python.
- Other info: Ideal for those passionate about finance and technology, eager to make an impact.
The predicted salary is between 43200 - 72000 £ per year.
My client, a T1 Investment bank with a renowned Electronic Execution team within the Cash Equities division, are looking for an experienced Quantitative Researcher to join them. In this role, you will play a critical part in shaping and advancing their electronic trading capabilities. You’ll collaborate with colleagues globally to share insights, improve platform interfaces, and ensure adherence to best practices.
You’ll be responsible for leading key projects from start to finish, including designing and implementing new models and supporting the full platform lifecycle. You’ll also drive enhancements to our trading algorithms and deliver robust, high-quality solutions that keep us at the forefront of electronic execution.
Key Responsibilities:- Drive and champion electronic execution initiatives within the Cash Equities team, fostering collaboration across global teams.
- Lead the development and deployment of new trading models and algorithmic solutions.
- Enhance and refine existing algorithms, adding new features and improving performance.
- Design and build analytic and implementation approaches, including system architecture and interfaces.
- Develop, test, and maintain high-quality C++, R, and Python code for new and existing tools.
- Create and support analytic tools for both team and business-wide use.
- Provide technical leadership and guidance, especially for complex issues requiring deep expertise and advanced analysis.
- Act as a mentor and escalation point for junior team members.
- A Master’s level or above education in a quantitative discipline or a PhD in a scientific or engineering field with a strong interest in financial modelling.
- Deep understanding of Cash Equities trading products and market microstructure.
- Proven experience developing code in C++, R, and Python.
- Strong quantitative and analytical skills, with a background in numerical techniques and machine learning (both supervised and unsupervised).
Snr. Quant Cash Equities Execution (City of London) employer: Bruin
Contact Detail:
Bruin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Snr. Quant Cash Equities Execution (City of London)
✨Tip Number 1
Network with professionals in the finance and quantitative research sectors. Attend industry conferences, webinars, or local meetups to connect with people who work in electronic execution or cash equities. This can help you gain insights into the role and potentially get referrals.
✨Tip Number 2
Familiarise yourself with the latest trends and technologies in electronic trading. Follow relevant blogs, podcasts, and publications to stay updated on advancements in algorithmic trading and market microstructure, which will demonstrate your passion and knowledge during interviews.
✨Tip Number 3
Showcase your coding skills by contributing to open-source projects or developing your own trading algorithms. This practical experience not only enhances your portfolio but also provides concrete examples to discuss during interviews, highlighting your technical expertise.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving and coding challenges related to quantitative finance. Websites like LeetCode or HackerRank can be great resources to sharpen your skills in C++, R, and Python, ensuring you're ready to impress potential employers.
We think you need these skills to ace Snr. Quant Cash Equities Execution (City of London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative research, electronic trading, and algorithm development. Emphasise your proficiency in C++, R, and Python, as well as any specific projects that showcase your skills in financial modelling.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their needs, particularly your experience in Cash Equities and your ability to lead projects. Mention any collaborative efforts you've been part of that demonstrate your teamwork skills.
Showcase Your Technical Skills: Include specific examples of your work with trading algorithms and quantitative models. If you have experience with machine learning techniques, be sure to mention this and how it has contributed to your previous roles or projects.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any errors or inconsistencies. A polished application reflects your attention to detail, which is crucial in a quantitative role. Consider asking a colleague or mentor to review your application as well.
How to prepare for a job interview at Bruin
✨Showcase Your Technical Skills
Be prepared to discuss your experience with C++, R, and Python in detail. Bring examples of projects where you've developed trading models or algorithms, and be ready to explain your thought process and the outcomes.
✨Understand Market Microstructure
Demonstrate a solid understanding of Cash Equities trading products and market microstructure. Be ready to discuss how these concepts influence electronic execution and the development of trading strategies.
✨Highlight Collaborative Experience
Since this role involves working with global teams, share examples of how you've successfully collaborated on projects. Emphasise your ability to communicate complex ideas clearly and work effectively in a team environment.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your quantitative and analytical skills. Practice explaining your approach to solving complex problems, especially those related to algorithm development and enhancements.
