Data Scientist - Macro

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 at the intersection of financial markets, data science and engineering, supporting the discovery, evaluation and integration of financial datasets used across quantitative research and trading. The role combines technical expertise with an understanding of Macro markets, working closely with Quantitative Researchers, Portfolio Managers and Traders to translate business requirements into practical data solutions. You will engage directly with external data providers, assess existing data assets and identify opportunities to expand the firm's data capabilities.

Your future role within QRT

Collaborate with Quantitative Researchers, Portfolio Managers and Traders to understand their data requirements and identify suitable datasets for research and trading strategies

Evaluate existing data assets and external vendor offerings, assessing coverage, quality, consistency and suitability for specific financial applications

Manage the discovery, evaluation and onboarding of new datasets, with a focus on Macro markets, including Rates, bonds, swaps, derivatives and alternative data

Engage directly with external data providers to understand their offerings, assess APIs and investigate data availability, structure and delivery mechanisms

Develop Python tools and data pipelines to extract, clean, normalise and analyse financial datasets from multiple sources

Investigate discrepancies across data providers, including differences in instrument identifiers, pricing conventions, timestamps and reference data

Maintain and improve the quality and consistency of existing datasets, proactively resolving issues and identifying opportunities to enhance data coverage

Collaborate with engineering teams to automate data ingestion, validation and integration processes, ensuring reliable delivery into research and trading environments

Your present skillset

Minimum 2 years of relevant professional experience in Data Science, Data Analysis, Data Engineering or a similar role within financial markets

Practical understanding of financial markets and instruments, with exposure to Macro, Fixed Income, Rates, Credit or related asset classes

Strong Python programming skills, including experience with data analysis libraries such as Pandas and NumPy

Good SQL skills and experience working with structured financial datasets

Experience sourcing, analysing and processing financial data, with an understanding of data quality, validation and consistency across multiple sources

Ability to understand financial concepts and communicate effectively with Quantitative Researchers, Portfolio Managers, Traders and external data vendors

Strong analytical and problem solving skills, with the ability to investigate unfamiliar datasets