• Use data to shape marketing strategies for millions of NAB customers.
• Apply advanced analytics and AI to solve meaningful customer and business challenges.
• Work with talented teams and senior stakeholders to turn insights into real outcomes.

Our people are customer obsessed. They work in close partnership to prioritise customer needs and deliver exceptional outcomes. This collaborative mindset enables innovation and builds enduring customer relationships supporting our ambition to be the most customer‑centric company in Australia and New Zealand. 

In the role of Consultant Data Science - Marketing, you will work closely with the Data and Digital Customer Decisioning Team, contributing to key business priorities and continuously improving how we serve our customers. 

This is a builder role. Many of the opportunities you will work on will begin without a predefined solution. You will help turn ambiguous opportunities into clear hypotheses, working systems and measurable outcomes through experimentation, engineering and evidence-based decision making.

You’ll make an impact each day by: 

• Designing and deploying AI solutions that improve customer decisioning and personalisation, including LLM, agentic, and machine learning systems.
• Developing rigorous evaluation methods that improve the quality, reliability and safety of AI systems.
• Collaborating with Data Engineering and Platform teams to take solutions from early discovery through to production.
• Contributing reusable tooling and capabilities that help scale AI development across the organisation.
• Working with large and complex datasets to understand customer behaviour, assess data quality, engineer features and prepare reliable inputs for machine learning and AI systems.
• Participating in design discussions and code reviews, collaborating to improve outcomes and team practices.

You’ll bring to this role: 

• Strong Python software engineering skills, with experience building modular, tested and maintainable production systems, not only exploratory notebooks.
• Strong machine learning fundamentals, including feature engineering, model selection, validation, evaluation, and the ability to identify leakage, bias and overfitting.
• Hands-on experience designing and building LLM applications or agentic workflows, with the ability and interest to develop across these areas.
• Practical experience using AI coding agents, or a demonstrated ability to adopt new development tools quickly while critically reviewing and testing generated code.
• Strong empirical judgement, including defining baselines, testing assumptions, analysing failures and balancing quality, reliability, safety, latency and cost.
• A collaborative, low-ego approach: you seek and respond constructively to feedback, challenge ideas respectfully and update your position when the evidence changes.

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.  

For details on the recruitment process, and accessibility, please visit https://www.nab.com.au/about-us/careers/apply-for-job.  To discuss adjustment requirements, please contact the NAB Careers team, via nab.careers@nab.com.au (please reference job number) or visit our Careers page through the link above for other contact options. 

Join NAB 

If you think this role is the right fit for you, we would love to hear from you. Please note candidate screening and interviews may be conducted prior to the closing date of the job advert. Unsolicited CVs from agencies will not be accepted.   

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