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For Companies At a Glance
- Tasks: Join our Data Search & Analytics team to leverage data for trading strategies.
- Company: Qube Research & Technologies is a global leader in quantitative investment management.
- Benefits: Enjoy a healthy work-life balance and a culture of innovation.
- Why this job: Be part of a collaborative team solving complex challenges in finance.
- Qualifications: 3+ years as a Data Scientist; advanced Python skills and a quantitative degree required.
- Other info: We value diversity and empower employees to achieve 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.
We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data at the firm.
Your future role within QRT
This team is integral to the firm’s success. As such, your responsibilities will include:
- Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and to inform discretionary trading decisions
- Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats
- Working with Engineers to automate and optimise your code, ensuring robust data extraction processes
- Managing the end-to-end process of onboarding new datasets
- Proactively solving data related problems to minimise time to production
- Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit
Your present skillset
- 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous
- Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering.
- Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
- Demonstratable interest in financial markets and the application of data in its analysis and understanding
- Experience working with both traditional and alternative financial datasets
- Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
- Ability to work in a high-performance, high-velocity environment
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 achieve a healthy work-life balance. #J-18808-Ljbffr
Data Scientist employer: Qube Research & Technologies
Contact Detail:
Qube Research & Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarize yourself with the specific datasets and tools used in quantitative finance. Understanding how to manipulate and analyze financial data will give you a significant edge during discussions with the team.
✨Tip Number 2
Showcase your programming skills by working on personal projects that involve data extraction and analysis. This not only demonstrates your technical abilities but also your passion for the field, which is crucial for a role at QRT.
✨Tip Number 3
Network with professionals in the quantitative finance space. Engaging with others in the industry can provide insights into the company culture at QRT and may even lead to referrals.
✨Tip Number 4
Prepare to discuss your experience with both traditional and alternative financial datasets. Being able to articulate how you've applied data science in real-world scenarios will be key in impressing the hiring team.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description for the Data Scientist position at Qube Research & Technologies. Understand the key responsibilities and required skills, especially the emphasis on collaboration with Quantitative Researchers and Traders.
Highlight Relevant Experience: In your application, make sure to highlight your 3+ years of experience as a Data Scientist or in a similar role. Emphasize any experience you have in quantitative finance, as this is advantageous for the position.
Showcase Technical Skills: Clearly demonstrate your advanced programming skills in Python and your proficiency with data handling libraries like Pandas and NumPy. Provide specific examples of how you've used these skills in previous projects.
Communicate Effectively: Since excellent communication skills are crucial for this role, ensure that your application reflects your ability to collaborate with various stakeholders. Use clear and concise language to convey your ideas and experiences.
How to prepare for a job interview at Qube Research & Technologies
✨Showcase Your Technical Skills
Be prepared to discuss your programming experience in Python, especially with libraries like Pandas and NumPy. You might be asked to solve a coding problem or explain how you've used these tools in past projects.
✨Demonstrate Your Understanding of Financial Markets
Since the role involves working with financial datasets, make sure to highlight your interest and knowledge in financial markets. Be ready to discuss how data analysis can impact trading decisions.
✨Prepare for Collaborative Scenarios
QRT values collaboration between teams. Think of examples from your past experiences where you successfully worked with researchers, traders, or engineers to solve complex problems.
✨Innovative Problem-Solving Approach
Be ready to share instances where you proactively solved data-related issues or innovated new methods for data extraction. This will demonstrate your ability to think critically and adapt in a fast-paced environment.
