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For Companies At a Glance
- Tasks: Lead quant trading strategies, focusing on machine learning and performance optimisation.
- Company: Join a forward-thinking firm in the heart of London, dedicated to excellence.
- Benefits: Enjoy a competitive salary, flexible working options, and a great benefits package.
- Why this job: Be part of an innovative culture that values creativity and impact in finance.
- Qualifications: Strong programming skills in Python, C++, and experience in quantitative research required.
- Other info: Work in a dynamic environment with flexible hours from day one.
The predicted salary is between 72000 - 108000 £ per year.
Job Requirements
- Machine learning, signal research, back testing & performance optimization
- Quantitative modeling
- Development and implementation of trading strategies
- Programming skills in Python, C++, Java, and experience with complex event processing
Company Details
You will be joining a progressive and exciting company committed to excellence. They offer an excellent salary and benefits package with flexible working options from day 1. My client is based in the City with flexible working hours.
Skills Needed
- Quantitative research
- Gauss
- Hull
- Options Theory
- C++
- Erlang
- F#
- Scala
- Haskell
- Django
- Python
- Twisted
- NoSQL
- Data Science
- and related skills.
Head of Quant Trading in London - Quant Capital (Basé à London) employer: Golden Bees
Contact Detail:
Golden Bees Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Quant Trading in London - Quant Capital (Basé à London)
✨Tip Number 1
Network with professionals in the quantitative trading field. Attend industry conferences, webinars, or local meetups to connect with people who work in similar roles. This can help you gain insights into the company culture and potentially get a referral.
✨Tip Number 2
Showcase your programming skills by contributing to open-source projects or creating your own projects on platforms like GitHub. This not only demonstrates your technical abilities but also your passion for coding and problem-solving.
✨Tip Number 3
Stay updated on the latest trends in quantitative finance and machine learning. Follow relevant blogs, podcasts, and research papers to discuss these topics during interviews, showing your enthusiasm and knowledge in the field.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm problems related to quantitative trading. Websites like LeetCode or HackerRank can be great resources to sharpen your skills and boost your confidence.
We think you need these skills to ace Head of Quant Trading in London - Quant Capital (Basé à London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in quantitative research, machine learning, and programming languages like Python and C++. Emphasise any relevant projects or roles that demonstrate your skills in trading strategy development.
Craft a Compelling Cover Letter: In your cover letter, express your passion for quantitative trading and how your background aligns with the company's goals. Mention specific experiences that showcase your expertise in signal research and performance optimisation.
Showcase Technical Skills: Clearly outline your programming skills and familiarity with tools and languages mentioned in the job description, such as C++, Java, and NoSQL. Providing examples of past projects can strengthen your application.
Highlight Soft Skills: While technical skills are crucial, don't forget to mention soft skills like teamwork, communication, and problem-solving. These are essential in a collaborative environment like Quant Capital.
How to prepare for a job interview at Golden Bees
✨Showcase Your Technical Skills
Make sure to highlight your programming skills in Python, C++, and Java during the interview. Be prepared to discuss specific projects where you've applied these languages, especially in relation to quantitative modelling and trading strategies.
✨Demonstrate Your Knowledge of Quantitative Research
Familiarise yourself with key concepts such as Gauss, Hull, and Options Theory. Be ready to explain how you have used these theories in past roles or projects, as this will show your depth of understanding in the field.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving abilities. Practice coding challenges or case studies related to back testing and performance optimisation to demonstrate your analytical skills.
✨Discuss Your Experience with Machine Learning
Since machine learning is a crucial part of the role, be prepared to discuss any relevant experience you have. Share examples of how you've implemented machine learning techniques in trading strategies or signal research.
