Master of Data Science in Quantitative Finance

Course content is comprised of 11 subjects, including six subjects from the Master of Quantitative Finance. Students engage with the in-depth study of financial market instruments, probability theory, and credit and market risk, among others, and diversify their skill sets with specialist study in machine learning, Bayesian methods and mathematical research. They also learn to apply their theoretical learning to industry-relevant assignments in areas such as derivative security pricing and hedging, valuation of financial instruments, market and credit risk measurement and management, and machine learning.

Graduates are highly sought after by leading financial institutions, management consulting companies, energy and mining companies, regulatory bodies, government organisations and other organisations seeking advanced data science and quantitative finance expertise. They can work as quantitative analysts, data scientists, data analysts, quantitative structurers, quantitative developers, forecasters, traders, financial engineers, market risk analysts, credit risk analysts, data engineers, data modellers and investment analysts.