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. 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 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