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- Tasks: Create innovative trading models and mentor junior researchers in a collaborative environment.
- Company: Join Qube Research & Technologies, a leader in quantitative investment management.
- Benefits: Enjoy a competitive salary, work-life balance initiatives, and opportunities for professional growth.
- Why this job: Make an impact in finance using cutting-edge technology and research methodologies.
- Qualifications: PhD in STEM preferred; experience in trading and knowledge of ML/AI is a plus.
- Other info: Be part of a diverse team that values innovation and collaboration.
The predicted salary is between 36000 - 60000 £ 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 our 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:
- Identify novel approaches and methodologies from academic and industrial research to produce predictive algorithmic trading models.
- Mentor and develop junior researchers through hands-on project guidance and internship co-supervision.
- Collaborate with cross-asset Research, Trading and Infrastructure teams.
- Deliver constructive feedback and conduct regular research project reviews, fostering the development of advanced technical and research skills.
- Build and nurture strong partnerships with leading academic institutions and research groups.
- Position the firm as a trusted partner for advanced research, fostering both applied and theoretical collaborations.
Prior experience in electronic, market-making, or proprietary trading environments. Education in STEM and Advanced Degree holder, with strong preference to PhD. Knowledge of ML/AI, deep learning, statistics, linear algebra, and optimisation. Familiarity with market microstructure. Strong educational and communication skills as well as a collaborative, mentoring-oriented mindset. Experience with Python and C++; exposure to hardware acceleration APIs (e.g. FPGA) is a plus.
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.
Seniority level: Not Applicable
Employment type: Full-time
Job function: Finance
HFT Quantitative Researcher – QRT Academy in England employer: Qube Research & Technologies
Contact Detail:
Qube Research & Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land HFT Quantitative Researcher – QRT Academy in England
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, conferences, or webinars related to quantitative research. The more you engage with others, the better your chances of landing that dream role at QRT.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your projects, research, and any cool algorithms you've developed. This is your time to shine and demonstrate how you can contribute to QRT’s innovative culture.
✨Practice Makes Perfect
Before any interviews, do some mock sessions with friends or mentors. Focus on technical questions and problem-solving scenarios relevant to quantitative research. This will help you feel more confident and prepared when it’s time to impress the team at QRT.
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to reach out and express their interest in joining QRT.
We think you need these skills to ace HFT Quantitative Researcher – QRT Academy in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the HFT Quantitative Researcher role. Highlight your relevant experience in electronic trading, ML/AI, and any projects that showcase your skills in Python or C++. We want to see how you can contribute to our innovative culture!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative research and how your background aligns with our mission at QRT. Don’t forget to mention any mentoring experience you have, as we value collaboration.
Showcase Your Projects: If you've worked on any interesting projects, especially those involving predictive algorithms or market microstructure, make sure to include them. We love seeing practical applications of your skills, so don’t hold back!
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 shows you’re keen on joining our team at QRT!
How to prepare for a job interview at Qube Research & Technologies
✨Know Your Algorithms
Make sure you brush up on your knowledge of algorithmic trading models. Be prepared to discuss specific methodologies you've used in the past and how they can be applied to QRT's approach. This shows that you understand their focus on predictive models and can contribute from day one.
✨Showcase Your Mentoring Skills
Since the role involves mentoring junior researchers, think of examples where you've guided others in your previous roles. Highlight your collaborative mindset and how you've fostered development in others. This will demonstrate that you're not just a strong researcher but also a team player.
✨Familiarise Yourself with Market Microstructure
Understanding market microstructure is crucial for this position. Do some research on how it impacts trading strategies and be ready to discuss its relevance during your interview. This will show that you’re not only technically proficient but also aware of the broader trading environment.
✨Prepare for Technical Questions
Expect technical questions related to Python, C++, and possibly hardware acceleration APIs. Brush up on your coding skills and be ready to solve problems on the spot. Practising common coding challenges can help you feel more confident and prepared.