Data Scientist - Macro

The role

You will work at the intersection of financial markets, data science and engineering. You will support the discovery, evaluation and integration of financial datasets used across quantitative research and trading.

What you will do

• Collaborate with Quantitative Researchers, Portfolio Managers and Traders to understand data requirements
• Evaluate existing data assets and external vendor offerings
• Manage the discovery, evaluation and onboarding of new datasets for Macro markets
• Engage directly with external data providers to assess APIs and data availability
• Develop Python tools and data pipelines to extract, clean, normalise and analyse financial datasets
• Investigate discrepancies across data providers
• Maintain and improve the quality and consistency of existing datasets
• Collaborate with engineering teams to automate data ingestion, validation and integration processes

Required qualifications

• 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
• Ability to understand financial concepts and communicate effectively with Quantitative Researchers, Portfolio Managers, Traders and external data vendors
• Strong analytical and problem solving skills
• Familiarity with external data providers, financial data platforms and API integration
• Ability to manage competing priorities, take ownership of data initiatives and collaborate effectively across technical and business functions
• Degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, Engineering or Finance

Nice to have

• a postgraduate qualification is beneficial
• Experience developing data pipelines, automating data workflows or supporting production data infrastructure is beneficial
• Knowledge of financial data concepts such as yield curves, instrument reference data, market data and pricing conventions is advantageous

Benefits

• initiatives and programs to enable employees achieve a healthy work-life balance

About the company

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. It is a technology and data driven group implementing a scientific approach to investing.