Bring your deep data science expertise to a standout role delivering production-ready models and data-led controls that make a real impact.

Work in a collaborative environment with highly talented and motivated colleagues who are passionate about winning together

Create impactful, data-led solutions that materially reduce fraud and scam losses across the customer lifecycle.

Make a real difference through the work you do for our customers and communities.

Our people are customer obsessed. They prioritise the needs and satisfaction of the customer above all else.  Our mindset fosters innovation and creates strong, lasting customer relationships as we strive to be the most customer centric company in Australia and New Zealand.

In the role of a Senior Data Consultant, you will join the Fraud Prevention & Detection team that’s doubling down on protecting the community and our customers.

Each day, you’ll go above and beyond to:

• Develop, deploy and optimise models across the fraud lifecycle (prevention, detection, intervention)
• Partner with Fraud Operations, Technology and Risk to embed analytics into live controls
• Monitor model performance, recalibrate thresholds and uplift effectiveness over time
• Apply fraud intelligence and emerging typologies to refine analytical approaches
• Communicate insights, assumptions and limitations in plain English to stakeholders
• Support prioritisation of analytics initiatives aligned to customer harm and loss outcomes
• Ensure compliance with risk, governance and regulatory expectations

We’re looking for the best and brightest to deliver the best for our customers. You’ll need:

• Advanced data science (ML, statistical modelling) applied to fraud use cases
• Extensive experience in data science / analytics in financial services (fraud focus)
• Proven delivery of models at scale with measurable outcomes
• Strong technical capability across modelling and analytics tools
• Strong fraud/scam domain expertise and evolving typologies
• Build and deploy production‑ready, scalable models embedded in controls
• Translate analytics into interventions that reduce customer harm and loss
• Influence across Fraud, Risk, Technology and Operations

A diverse and inclusive workplace works better for everyone

We know that our people make us who we are. That’s why we have built a culture of equity and respect - where everyone feels valued and appreciated for being their authentic selves. In partnership with our multiple Employee Resource Groups (ERGs), we continue to foster an inclusive environment, where all NAB colleagues’ unique backgrounds and identities are understood, respected and celebrated. We are committed to providing an environment where you can work your way.

• Develop, deploy and optimise models across the fraud lifecycle (prevention, detection, intervention)
• Partner with Fraud Operations, Technology and Risk to embed analytics into live controls
• Monitor model performance, recalibrate thresholds and uplift effectiveness over time
• Apply fraud intelligence and emerging typologies to refine analytical approaches
• Communicate insights, assumptions and limitations in plain English to stakeholders
• Support prioritisation of analytics initiatives aligned to customer harm and loss outcomes
• Ensure compliance with risk, governance and regulatory expectations

• Advanced data science (ML, statistical modelling) applied to fraud use cases
• Strong technical capability across modelling and analytics tools
• Strong fraud/scam domain expertise and evolving typologies
• Build and deploy production‑ready, scalable models embedded in controls
• Translate analytics into interventions that reduce customer harm and loss
• Influence across Fraud, Risk, Technology and Operations

• Extensive experience in data science / analytics in financial services (fraud focus)
• Proven delivery of models at scale with measurable outcomes