At a Glance
- Tasks: Join a dynamic team to develop and implement cutting-edge trading strategies.
- Company: A leading global hedge fund known for innovative investment across diverse markets.
- Benefits: Enjoy competitive salaries, performance bonuses, and a collaborative work culture.
- Other info: Opportunity to expand platform capabilities and tackle exciting challenges.
- Why this job: Work with brilliant minds and make a real impact in finance technology.
- Qualifications: 5+ years in Quant Development, strong Python/C++ skills, and a relevant degree.
A leading systematic hedge fund, investing across a variety of financial markets in multiple locations, my client is seeking a creative problem-solver to be the next Quant Developer in their growing Model Implementation team. This team is comprised of technical and hands-on builders, each wearing multiple hats, and in this role you'll be expected to do the same. Working very closely with Researchers and PMs on the team, your primary responsibility will be the distributed real-time trading system for computing signals, and targeting positions for various strategies. You'll also own the design and production implementation of new strategies, lead efforts to identify and tackle platform bottlenecks, as well as adding expanding the platform capabilities to new asset classes.
The successful Quant Developer will have a strong work ethic, fantastic multi-tasking ability and a good sense of accountability.
Requirements
- Minimum 5+ years of Quant Developer experience (or similar position)
- Strong coding experience in Python and C++, with outstanding debugging and analytical skills
- Experience with Python data science stack, e.g. Pandas/Numpy/Scikit-learn
- Keen proponent of writing automated tests
- BS/MS/PhD in Computer Science (or equivalent)
Benefits
- Competitive base salaries and performance-based bonuses
- Very collaborative culture, ideas are implemented
- Work with passionate, forward-thinking, incredibly smart people
If you feel you are a strong match for this role, please don't hesitate to get in touch.
Daniel Readman
daniel.readman@oxfordknight.co.uk
+44 (0)203 475 7190
linkedin.com/in/daniel-readman-a410b515a
Quant Developer (Python/C++) - Model Implementation - London- Global Hedge Fund employer: Oxford Knight
As a leading systematic hedge fund based in London, we pride ourselves on fostering a collaborative and innovative work culture where creative problem-solvers thrive. Our Quant Developers enjoy competitive compensation packages exceeding £300k, alongside opportunities for professional growth while working with some of the brightest minds in the industry. Join us to be part of a dynamic team that values your ideas and contributions in shaping cutting-edge trading strategies.
Contact Details:
Oxford Knight Recruitment Team
daniel.readman@oxfordknight.co.uk
StudySmarter Expert Advice🤫
We think this is how you could land Quant Developer (Python/C++) - Model Implementation - London- Global Hedge Fund
✨Tip Number 1
Network with professionals in the hedge fund industry, especially those who work as Quant Developers. Attend relevant meetups or conferences where you can connect with people from similar backgrounds and share your passion for quantitative finance.
✨Tip Number 2
Showcase your coding skills by contributing to open-source projects or creating your own projects that demonstrate your expertise in Python and C++. This will not only enhance your portfolio but also give you practical experience that can impress potential employers.
✨Tip Number 3
Prepare for technical interviews by practising coding challenges that focus on algorithms and data structures. Familiarise yourself with common problems faced in quantitative finance to demonstrate your problem-solving abilities during the interview process.
✨Tip Number 4
Stay updated on the latest trends and technologies in quantitative finance and model implementation. Follow industry leaders on social media and read relevant publications to ensure you can engage in informed discussions during interviews.
We think you need these skills to ace Quant Developer (Python/C++) - Model Implementation - London- Global Hedge Fund
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in Quant Development, particularly your coding skills in Python and C++. Emphasise any relevant projects or roles that showcase your problem-solving abilities and multi-tasking skills.
Craft a Strong Cover Letter:In your cover letter, express your enthusiasm for the role and the company. Mention specific experiences that align with the job description, such as your familiarity with the Python data science stack and your approach to automated testing.
Showcase Relevant Projects:If you have worked on projects related to distributed real-time trading systems or have experience in implementing new strategies, be sure to include these in your application. Highlight your contributions and the impact they had on the project.
Proofread Your Application:Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is crucial for a Quant Developer role.
How to prepare for a job interview at Oxford Knight
✨Showcase Your Technical Skills
Make sure to highlight your coding experience in Python and C++. Be prepared to discuss specific projects where you've implemented complex algorithms or tackled debugging challenges, as this will demonstrate your hands-on capabilities.
✨Demonstrate Problem-Solving Abilities
As a Quant Developer, you'll need to be a creative problem-solver. Prepare examples of how you've identified and resolved bottlenecks in previous projects, especially in real-time systems or trading platforms.
✨Emphasise Collaboration
This role requires working closely with Researchers and PMs. Be ready to discuss your experience in collaborative environments and how you’ve contributed to team success, showcasing your ability to wear multiple hats.
✨Prepare for Technical Questions
Expect technical questions related to the Python data science stack, such as Pandas, Numpy, and Scikit-learn. Brush up on these tools and be ready to explain how you've used them in your work, particularly in relation to automated testing.
