Data Scientist (Fraud)

Kasada · Sydney

Lever Posted May 18, 2026 First seen May 26, 2026
About Kasada

Join us in stopping bad bots, for good! Kasada protects millions of online users everyday. Founded to stop automated bot attacks, we believe the internet should be a safe place for everyone. Bad bots are highly destructive. They take over accounts, steal content, overload systems and infrastructure and cause billions of dollars in damages every year. Seeking to restore trust in the internet, Kasada stops bots at the very first request including those that have never been seen before.

We’ve grown from a few friends working out of a shipping container under the Sydney Harbour Bridge to now operating globally, we’re spread across the world protecting some of the most well-known brands on the face of the earth.

We’re an innately curious team that’s not afraid to bring bold ideas to create better ways of solving problems. We’re looking for people who are passionate about solving some of the most difficult and pressing cybersecurity issues, while having fun doing it!

Kasada has an exciting opportunity to join our team responsible for defending our customers against fraud and malicious automation. Attackers use a number of ever changing toolsets to launch highly costly attacks on our customers. As the first Data Scientist in the Account Intelligence team, you will work in a high energy team applying predictive modelling and statistical methods to help us defeat adversaries. A critical part of this role involves partnering with engineering, research, and security operations to turn data science work into production defences that stand up against real attackers.

We are looking for a hands-on data scientist to help shape the predictive detection capabilities within Account Intelligence and the way we tell legitimate users apart from adversaries. While your focus may shift from time to time, you are expected to remain technical and hands on across the full model lifecycle, from exploring data and building models through to evaluating how your work performs once adversaries start adapting. You will be supported by experienced engineering and research teams to take your work from notebook to production.