At a Glance
- Tasks: Develop and enhance Python libraries for trading strategies and support user documentation.
- Company: Join Qube Research & Technologies, a global leader in quantitative investment management.
- Benefits: Enjoy a flexible work environment with initiatives for a healthy work-life balance.
- Why this job: Be part of an innovative team solving complex challenges in finance with cutting-edge technology.
- Qualifications: Strong Python skills, excellent communication, and a solid understanding of financial concepts required.
- Other info: QRT values diversity and promotes a collaborative culture for collective success.
The predicted salary is between 43200 - 72000 £ per year.
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT This team works on the end to end solution for signal based extra-day and intra-day strategies at QRT. The python library/framework with which researchers can perform their research and develop their strategies. The on-ramp pipelines and process for submitting, backtesting and validating those strategies to trading. The platform which runs all those strategies in production, including the scaling and monitoring of that platform. Your present skillset Strong python development skills, both exercised for the Python Integrator library itself, and for the tooling around the platform. Excellent written and verbal communication skills, as we have a strong focus on user facing documentation and support. Advanced financial functional knowledge, to be able to design the features the researchers and traders need in the library. Architectural skills to help design an ever evolving platform always one step ahead of the needs in terms of scaling. Great CI/devops mindset to help the team achieve maximal efficiency and the product to reach an excellent level of quality. Rust/C high performance computing skills to help always improve the performance of the hotspots of the different components. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees to achieve a healthy work-life balance. #J-18808-Ljbffr
Quantitative Developer - Python Integrator employer: Qube Research & Technologies Limited
Contact Detail:
Qube Research & Technologies Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer - Python Integrator
✨Tip Number 1
Familiarise yourself with QRT's approach to quantitative investing. Understanding their scientific methodology and how they integrate technology with trading will help you align your skills with their needs.
✨Tip Number 2
Brush up on your Python skills, especially in the context of developing libraries and frameworks. Consider contributing to open-source projects or building your own tools to showcase your expertise.
✨Tip Number 3
Network with professionals in the quantitative finance space. Attend relevant meetups or webinars to connect with people who work at QRT or similar firms, as personal referrals can significantly boost your chances.
✨Tip Number 4
Prepare to discuss your architectural skills and CI/devops mindset during interviews. Be ready to share examples of how you've improved efficiency or quality in past projects, as this aligns closely with QRT's goals.
We think you need these skills to ace Quantitative Developer - Python Integrator
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong Python development skills and any relevant experience with quantitative finance. Emphasise your architectural skills and CI/devops mindset, as these are crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, explain why you are interested in Qube Research & Technologies and how your skills align with their mission. Mention your experience with user-facing documentation and support, as well as your ability to work collaboratively.
Showcase Relevant Projects: If you have worked on projects involving Python libraries or financial tools, be sure to include them in your application. Describe your role and the impact of your contributions, particularly in relation to scaling and performance improvements.
Highlight Communication Skills: Since excellent written and verbal communication skills are essential for this position, provide examples of how you've effectively communicated complex ideas or supported users in previous roles. This will demonstrate your fit for the collaborative culture at QRT.
How to prepare for a job interview at Qube Research & Technologies Limited
✨Showcase Your Python Skills
Be prepared to discuss your experience with Python in detail. Highlight specific projects where you've developed libraries or frameworks, and be ready to demonstrate your coding skills through practical tests or coding challenges.
✨Communicate Clearly
Since excellent communication is key for this role, practice explaining complex technical concepts in simple terms. Be ready to discuss how you would document user-facing features and support users effectively.
✨Demonstrate Financial Knowledge
Brush up on your understanding of financial concepts relevant to quantitative trading. Be prepared to discuss how your knowledge can help design features that meet the needs of researchers and traders.
✨Emphasise CI/DevOps Mindset
Discuss your experience with continuous integration and DevOps practices. Share examples of how you've implemented these methodologies to improve efficiency and quality in previous projects.