Build and optimize data pipelines for quant research and trading teams using Python, NumPy, Pandas, and HDF5 to process large datasets and support trading strategy development.
As a quantitative data engineer you will be working together with the quantitative research and trading teams, as well as with the trading strategy developers to:
source and cleanse data, develop and maintain data pipelines as required by quant research and trading
assist with researching trading opportunities by extracting information from datasets, visualizing the results, generating automated reports, and communicating them with traders; develop, deploy, and maintain interactive and packaged reports that will directly influence trading strategies
performance-tune existing applications and processes, improve existing codebases and data flows to allow for efficient processing of large datasets
What we’re looking for
Minimum requirement is a Bachelor’s degree in a quantitative discipline such as mathematics, physics, or computer science. Postgraduate degree is preferred
Experience with the Python data science stack e.g., NumPy, Pandas, Matplotlib
Experience with numeric data storage methodologies, e.g., hdf5
Experience processing large datasets
Experience working in a Linux environment
Ability to understand mathematical algorithms and develop high-performance implementations
Strong interpersonal and communication skills for interacting with traders, quantitative analysts, and other software developers
Interest in areas such as capital markets, probability, game theory and the application of quantitative solutions to these areas is a plus