At a Glance
- Tasks: Design and develop financial datasets to support trading strategies using Python.
- Company: Join Qube Research & Technologies, a global leader in quantitative investment management.
- Benefits: Enjoy a healthy work-life balance, competitive salary, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace focused on collective success and employee empowerment.
- Why this job: Make an impact by solving complex challenges in a collaborative and innovative environment.
- Qualifications: 2-5 years in data roles with strong Python skills and financial market knowledge.
The predicted salary is between 63000 - 77000 £ 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.
You will work within a data focused function supporting Quantitative Researchers, Traders and other stakeholders across the firm. The role focuses on designing and developing financial datasets that support systematic strategies and trading decisions, with particular emphasis on market data, pricing datasets and reference data. You will combine financial market knowledge with Python and data engineering skills to build and own the automated production pipelines that create and maintain these datasets.
Your future role within QRT:
- Collaborate with Quantitative Researchers and Traders to design financial datasets that support systematic strategies and trading decisions.
- Develop Python code to extract, clean, normalise and aggregate data from a range of financial market data sources.
- Design, build and maintain automated data pipelines covering sourcing, extraction, transformation, validation and delivery.
- Develop and maintain pricing and reference datasets across financial instruments and markets.
- Investigate and resolve data quality and production issues to improve the reliability and availability of datasets.
- Evaluate and implement new approaches to data extraction, processing and onboarding.
- Take ownership of production data workflows and evolve them as data requirements, systems and business priorities change.
Requirements:
- 2 to 5 years of experience in a data focused role working with financial or market data.
- Strong understanding of financial markets and instruments, including the behaviour and characteristics of pricing and reference datasets.
- Advanced Python programming skills, including experience with data processing libraries such as Pandas or Polars.
- Experience designing, building and maintaining automated production data pipelines.
- Strong data analysis and problem solving skills, with the ability to investigate data quality issues and understand their underlying causes.
- Experience working with market data platforms and APIs from providers such as Bloomberg or LSEG is beneficial, including products such as Datastream, DataScope Select, Real Time, BPIPE or Data License.
- Postgraduate degree in Mathematics, Physics, Engineering, Computer Science or another quantitative discipline.
- Strong communication skills with the ability to collaborate effectively with Quantitative Researchers, Traders and other stakeholders.
- Ability to operate effectively as priorities, systems, projects and business requirements evolve.
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.
Data Scientist - Market Data in England employer: Qube Research & Technologies
At Qube Research & Technologies, we pride ourselves on fostering a dynamic work culture that encourages innovation and collaboration. As a Platform Security Engineer, you will have the opportunity to work in a cutting-edge environment where your contributions directly impact our security posture, while also benefiting from professional growth opportunities and a commitment to employee well-being. Located in a vibrant tech hub, we offer a unique blend of challenging projects and a supportive team atmosphere, making us an excellent employer for those seeking meaningful and rewarding work.
Contact Details:
Qube Research & Technologies Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Market Data in England
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Qube Research & Technologies!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist - Market Data at Qube Research & Technologies.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Qube Research & Technologies.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist - Market Data at Qube Research & Technologies, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Scientist - Market Data in England
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Qube Research & Technologies, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Qube Research & Technologies. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Qube Research & Technologies
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Qube Research & Technologies!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
