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 with strong experience in index data. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of index data across the firm's systematic strategies.

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 and maintain index and ETF datasets that drive systematic strategies and inform discretionary trading decisions

• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats, including index constituent data, benchmark compositions, weightings, rebalancing schedules, ETF holdings and flows, and associated reference data

• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes

• Managing the end-to-end process of onboarding new index and ETF datasets, including equity indices, fixed income indices, ETFs, custom baskets, and related benchmark products

• 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

• 2+ years of experience as a Data Scientist (or similar position) working with index or ETF data, benchmark data, or index-linked financial products; experience in a buy-side quantitative finance role is strongly preferred

• Solid understanding of index construction, constituent methodology, rebalancing mechanics, ETF structure and flows, and the role of benchmarks in systematic and portfolio-level strategies

• 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

• Proven experience building and managing data pipelines end-to-end; from sourcing and extraction through to cleaning, processing, and delivery

• 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.