Quantitative Analyst - Bayesian ML & Markets

RGIT Australia; City of Melbourne; On-site; AUD 150,000 - 210,000; Full time

Job summary

RGIT Australia seeks a Quantitative Analyst for a Systematic Hedge Fund role in Melbourne. You will design and implement predictive models and work with a small, agile team across data science and software engineering to translate research into production quality trading systems.

The role values rigorous empirical methods, deep coding expertise in MATLAB/Python/C/Fortran, and a PhD or Masters in a quantitative field, with opportunities to impact real trading decisions and market understanding.

Qualifications

• A Masters or PhD in Physics, Atmospheric Science, Mathematics, Computer Science, Engineering or an equivalent discipline.
• A strong academic foundation with a passion for truth and the scientific method.
• A high level of initiative and self-motivation.
• Excellent coding skills and deep experience with large datasets (MATLAB, Python, C, Fortran or similar).

Responsibilities

• Design and develop predictive models, working closely with quantitative developers to bring them into production.
• Apply rigorous, empirical methods — Bayesian inference, statistical testing, and sound theoretical foundations — to real trading problems.
• Explore new techniques across data science, machine learning, stochastic processes, optimisation and signal processing.
• Work with large, complex datasets, and contribute to how we collect, structure and interpret them.
• Collaborate directly with developers and other researchers to turn ideas into deployed, working models, and to build a deep, shared understanding of the markets we trade.

Education

Masters or PhD in Physics, Atmospheric Science, Mathematics, Computer Science, Engineering or an equivalent discipline

Tools

MATLAB

Python

C

Fortran

Job description

RGIT Australia seeks a Quantitative Analyst for a Systematic Hedge Fund role in Melbourne. You will design and implement predictive models and work with a small, agile team across data science and software engineering to translate research into production quality trading systems.

The role values rigorous empirical methods, deep coding expertise in MATLAB/Python/C/Fortran, and a PhD or Masters in a quantitative field, with opportunities to impact real trading decisions and market understanding.