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- Tasks: Conduct innovative research to uncover market anomalies and enhance trading strategies.
- Company: Join Cubist Systematic Strategies, a leader in systematic trading and data-driven insights.
- Benefits: Competitive salary, access to cutting-edge technology, and opportunities for professional growth.
- Why this job: Make a real impact in the finance world with your analytical skills and creativity.
- Qualifications: Strong background in quantitative fields and experience in signal research.
- Other info: Collaborative environment with a focus on ethical standards and continuous learning.
The predicted salary is between 36000 - 60000 £ per year.
ABOUT CUBIST
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
ROLE/RESPONSIBILITIES
- Perform rigorous and innovative research to discover systematic anomalies in global macro markets (futures, FX, etc.)
- Perform feature engineering with price-volume, order book and alternative data at intraday to daily horizons in mid frequency trading space
- Perform feature combination and monetization using various modeling techniques
- Manage the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
- Maintain and improve portfolio trading in a production environment
- Contribute to the analysis framework for scalable research
REQUIREMENTS
- Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics
- 2+ years of signal research experience in macro trading as part of a trading team
- Prior professional experience with feature engineering, modeling, or monetization
- Ability to efficiently format and manipulate large, raw data sources
- Demonstrated proficiency in Python, R, or C/C++. Familiarity with data science toolkits, such as scikit-learn, Pandas
- Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques
- Collaborative mindset with strong independent research abilities
- Commitment to the highest ethical standards
Quantitative Researcher in City of London employer: Point72 Careers
Contact Detail:
Point72 Careers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher in City of London
✨Tip Number 1
Network like a pro! Reach out to professionals in the quantitative finance space on LinkedIn or at industry events. We can leverage our connections to get insights and maybe even referrals that could land us an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your research projects, especially those involving feature engineering and modelling. We can use this to demonstrate our expertise and make a lasting impression during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python, R, or C/C++ skills. We should practice coding challenges and be ready to discuss our previous projects in detail, highlighting our problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! It’s a great way to ensure our application gets noticed. Plus, we can tailor our approach based on the specific role and showcase how we fit into the Cubist Systematic Strategies team.
We think you need these skills to ace Quantitative Researcher in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Researcher role. Highlight your experience in signal research, feature engineering, and any relevant programming skills. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about systematic trading and how your skills can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see your hands-on experience with data manipulation and modelling techniques.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at Cubist!
How to prepare for a job interview at Point72 Careers
✨Know Your Data
Make sure you’re well-versed in the data sources relevant to the role. Familiarise yourself with how to manipulate and format large datasets, as this will likely come up during the interview. Be ready to discuss your experience with Python, R, or C/C++ and how you've used these tools in past projects.
✨Showcase Your Research Skills
Prepare to talk about specific examples of your signal research experience. Highlight any innovative approaches you've taken to discover systematic anomalies in macro markets. This is your chance to demonstrate your analytical thinking and problem-solving skills, so have a few case studies ready to share.
✨Brush Up on Your Statistics
Since the role requires a strong command of applied and theoretical statistics, make sure you can confidently discuss key concepts. Be prepared to answer questions on linear algebra and machine learning techniques, as well as how you’ve applied them in your previous work.
✨Collaborate and Communicate
Emphasise your collaborative mindset and independent research abilities. Be ready to discuss how you’ve worked within a team to manage the research pipeline from idea generation to production implementation. Communication is key, so practice articulating your thoughts clearly and concisely.
