Requirements

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, engineers, management, and external vendors
Ability to work in a high-performance, high-velocity environment

What you'll be doing

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 optimize your code, ensuring robust data extraction processes
Managing the end-to-end process of onboarding new datasets
Proactively solving data-related problems to minimize time to production
Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit

QRT is an equal opportunity employer fostering diversity
Encourages open, respectful working environment for collective success
Offers initiatives and programs to enable employees to achieve a healthy work-life balance