Location - Sydney (5 days in office)

Build statistical models. Challenge market pricing. Solve problems most investors never see.

Most data science roles optimise marketing campaigns, predict customer behaviour or build dashboards. Here we're partnering with a highly sophisticated quantitative investment firm that has built one of Australia's most advanced research environments.

The team develops large-scale statistical models that price thousands of financial instruments, identify pricing inefficiencies and transform quantitative research into production-grade systems used by investment professionals every day. Average investment duration is usually between 2-8 days, but trading within the day is a regular occurence.

You'll work alongside mathematicians, statisticians, software engineers and quantitative researchers in an environment where intellectual curiosity and technical excellence are genuinely valued.

This is an opportunity for someone who enjoys solving difficult mathematical problems and wants their work to have an immediate real-world impact.

What you'll be doing

- Design statistical and machine learning models for complex financial datasets.
- Build scalable research and pricing frameworks.
- Work with large, messy datasets from multiple market sources.
- Develop and back-test predictive models.
- Turn research ideas into production-quality code.
- Improve the performance, robustness and scalability of existing quantitative models.
- Create data visualisations that help communicate complex research findings.
- Collaborate with researchers,



engineers and investment professionals on new modelling techniques.

Candidate backgrounds:
- You'll likely have a degree in - Mathematics, Statistics, Actuarial Studies, Computer Science, Physics, Engineering, Econometrics.
- 1-3 years of experience (with some flex) post Bachelors Degree.
- Please note we aren't considering PHDs or candidates with Quantitative Finance degress.

You'll ideally bring:
- Exceptional academic results. Minimum 99ATAR, Minimum High Distinction Average.
- Strong Python and/or R programming skills.
- SQL and data engineering capability.
- Experience working with large datasets.
- Excellent statistical modelling ability.

Experience in financial markets isn't essential. Strong quantitative thinking is.

You'll probably enjoy this role if...

You read research papers for fun.

You enjoy proving why a model is wrong before trying to improve it.

You care about elegant code as much as accurate mathematics.

You'd rather spend your day solving difficult optimisation problems than sitting in stakeholder meetings.

You like environments where performance is measured by the quality of your thinking.

Why consider it?

You'll join a small team of exceptionally capable quantitative professionals working on genuinely challenging research problems with direct commercial impact.

This is a role where your models won't sit on a shelf—they'll influence investment decisions, evolve continuously and be tested against real markets.

If you're looking for an setting where technical excellence matters more than hierarchy, we'd love to hear from you.

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