
Qube Research & Technologies · London
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a ...
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:
discretionary trading decisions
Your present skillset
advantageous
traders, engineers, management, and external vendors
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.
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 a strong fixed income background. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data across the firm's fixed income strategies and beyond. 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, particularly within fixed income, to design 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 fixed income market data, reference data, and pricing feeds * Working with Engineers to automate and optimise your code, ensuring robust data extraction processes * Managing the end-to-end process of onboarding new datasets, with a focus on fixed income instruments such as bonds, rates, credit, and derivatives * 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 fixed income data; experience in a buy-side quantitative finance role is strongly preferred * Solid understanding of fixed income markets and instruments including bonds, interest rates, credit, yield curves, or related derivatives * 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.
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.
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 researchers, traders and engineering teams across the firm. The role focuses on designing and developing datasets that support systematic strategies and trading decisions, while improving the robustness and scalability of data onboarding processes. You will collaborate closely with technical and business stakeholders to help accelerate the use of both traditional and alternative datasets. Your future role within QRT * Collaborate with quantitative researchers and traders to design datasets supporting systematic strategies and trading decisions * Develop code to extract, clean and aggregate data from a wide range of structured and unstructured sources * Build and maintain robust data pipelines covering sourcing, transformation and delivery workflows * Work with engineering teams to automate and optimise data extraction and processing systems * Investigate and resolve data related issues to reduce time to production * Evaluate and implement new approaches for data extraction and onboarding Your present skillset * 2 or more years of experience as a Data Scientist or in a similar data focused role working with financial market data * Experience within quantitative finance or buy side environments is beneficial * Strong understanding of financial markets and financial instruments * Postgraduate degree in Mathematics, Physics, Engineering or another quantitative discipline * Advanced Python programming skills, including experience with libraries such as Pandas and Polars * Proven experience building and managing end to end data pipelines * Experience working with both traditional and alternative datasets * Strong communication skills with the ability to collaborate across research, trading, engineering and external stakeholders * Ability to operate effectively in a fast paced 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.