Advanced Analytics Senior Analyst - Customer Engagement & Yello for Business

• Use advanced analytics to create better customer experiences

• Turn complex data into smarter business decisions

• Build smarter ways to recognise and reward customers

See Yourself in our Team

Business Bank Advanced Analytics & Data helps CommBank understand its business customers and create more relevant, meaningful experiences through data, analytics and technology. Within the Customer Analytics & Engagement team, we work across customer insights, personalisation, next-best conversations and decisioning, partnering with Digital, Marketing, Product and Technology teams. This role supports Yello for Business, CommBank’s customer recognition program for business customers. You’ll work across analytics, predictive modelling, customer offers and communications, with the opportunity to see your work translate directly into customer experiences.

Your Impact and Contribution

As a Senior Advanced Analytics Analyst, you’ll use data and predictive modelling to help Business Bank better recognise, reward and engage its customers.

You’ll work with large and diverse datasets to understand customer behaviour, needs, product holdings, profitability and engagement, then turn those insights into smarter decisions and more personalised experiences.

You will:

• Use SQL and Python to analyse large, complex datasets and build scalable analytical solutions.

• Build and apply predictive models to identify customer needs, anticipate behaviours and improve personalisation.

• Analyse customer behaviour, product holdings, profitability and interactions to identify commercial and customer opportunities.

• Use data to shape customer offers, communications and next-best conversations.

• Build and improve controls, automation, dashboards and self-service analytics that help Yello for Business operate effectively.

• Identify and resolve data quality issues before they affect customers or downstream activity.

• Partner with Digital, Marketing, Product, Technology and business teams to turn analytical insights into practical outcomes.

• Explore how AI, machine learning and agentic tools can improve modelling, decisioning and productivity.

What You’ll Bring

You’re curious, commercially minded and motivated by understanding customers through data. You’re comfortable tackling open-ended problems, challenging assumptions and deciding the right analytical approach.

You’ll bring:

• Strong SQL and Python capability, including experience working with large datasets.

• Hands-on experience building predictive models, from problem framing and feature development through to evaluation and implementation.

• Experience using analytics or modelling to improve customer experience, personalisation, marketing, pricing, risk or commercial outcomes.

• Strong analytical curiosity and the confidence to explore unfamiliar data and ambiguous problems.

• Experience communicating complex analysis and influencing stakeholders.

• Experience visualising insights or model outputs using tools such as Tableau, Power BI, R Shiny or Streamlit.

• Practical knowledge of machine learning, AI and emerging analytical tools, with sound judgement about when to use them.

• A degree in Actuarial Studies, Economics, Finance, Statistics, Mathematics, Science or another relevant discipline would be well regarded. Experience in customer rewards, communications or commercial insights is valuable, but not essential.

This is a strong opportunity to deepen your understanding of CommBank data, strengthen your predictive modelling capability and grow into more advanced analytics work. The team values curiosity, self-learning and giving people space to build capability.

Working With Us

At CommBank, we're committed to creating an accessible, inclusive and respectful workplace. If you require support or adjustments, please let us know.

We welcome applications from people of all backgrounds and we're particularly committed to making a positive difference for Aboriginal and/or Torres Strait Islander Peoples. For support, please contact 1800 989 696.