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For Companies At a Glance
- Tasks: Join our Data Search & Analytics team to enhance data-driven investment strategies.
- Company: Qube Research & Technologies is a global leader in quantitative investment management.
- Benefits: Enjoy a collaborative culture, flexible work options, and initiatives for work-life balance.
- Why this job: Be part of an innovative team solving complex challenges in finance with cutting-edge technology.
- Qualifications: 3+ years as a Data Scientist; postgraduate degree in a quantitative field; Python proficiency required.
- Other info: We value diversity and promote a respectful, open workplace 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.
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 the trading desk to design and implement their data pipelines
- Collaborating with data engineers to onboard relevant datasets for the desk within QRT
- Implementing data transformations to produce high added-value datasets used for investment decisions
- Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats
- 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
- Demonstrable 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 - Commodities employer: Qube Research & Technologies
Contact Detail:
Qube Research & Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Commodities
✨Tip Number 1
Familiarise yourself with Qube Research & Technologies' approach to data-driven investing. Understanding their culture of innovation and how they leverage data in trading will help you align your skills and experiences with their needs.
✨Tip Number 2
Brush up on your Python programming skills, especially with libraries like Pandas and NumPy. Being able to demonstrate your proficiency in these tools during discussions can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your experience with both traditional and alternative financial datasets. Be ready to share specific examples of how you've used data to drive investment decisions or solve complex problems in previous roles.
✨Tip Number 4
Highlight your collaborative skills by preparing examples of how you've worked effectively with cross-functional teams. QRT values communication and teamwork, so showcasing your ability to collaborate with researchers, traders, and engineers will be beneficial.
We think you need these skills to ace Data Scientist - Commodities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience as a Data Scientist, particularly in quantitative finance. Emphasise your programming skills in Python and familiarity with data handling libraries like Pandas and NumPy.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for financial markets and your ability to collaborate effectively with various teams. Mention specific projects or experiences that demonstrate your problem-solving skills and innovative mindset.
Showcase Relevant Projects: If you have worked on any projects related to data pipelines, data transformations, or financial datasets, include them in your application. Provide brief descriptions of your role and the impact of these projects.
Highlight Communication Skills: Since the role requires collaboration with multiple stakeholders, emphasise your communication skills in both your CV and cover letter. Provide examples of how you've successfully worked with researchers, traders, and engineers in the past.
How to prepare for a job interview at Qube Research & Technologies
✨Showcase Your Technical Skills
Make sure to highlight your programming experience, especially in Python and data handling libraries like Pandas and NumPy. Be prepared to discuss specific projects where you've implemented data pipelines or transformations, as this will demonstrate your hands-on expertise.
✨Understand the Financial Context
Since QRT operates in the financial sector, it's crucial to show your understanding of financial markets and how data analysis plays a role in investment decisions. Brush up on relevant financial concepts and be ready to discuss how your skills can contribute to their trading strategies.
✨Emphasise Collaboration
QRT values teamwork, so be prepared to discuss your experience working with different stakeholders, such as traders and engineers. Share examples of how you've successfully collaborated in past roles to solve complex problems or enhance data processes.
✨Demonstrate Problem-Solving Abilities
Be ready to talk about specific challenges you've faced in data-related projects and how you approached solving them. Highlight any innovative methods you've used for data extraction or onboarding, as this aligns with QRT's culture of innovation.
