Advanced Analytics Manager – Customer Decisioning & Personalisation

• Work with cutting-edge AI, advanced analytics and customer decisioning tools
• Thrive in an inclusive, high-performing and highly collaborative culture
• Enjoy the flexibility of hybrid working with modern, central offices

Retail Advanced Analytics & Data (RAAD) partners closely with Retail Banking Services to deliver best practice across data, advanced analytics, AI and customer decisioning. We operate in a fast-paced, high-impact environment where analytics directly shapes customer experiences, business outcomes and growth.

Our team sits at the intersection of customer analytics, advanced decisioning and AI-enabled experimentation. We work across ventures and propositions designed to solve real customer problems, using rich customer data and analytical techniques to design, optimise and scale Next Best Conversations.

Our work goes beyond reporting and analysis. We partner closely with product, marketing, risk, compliance and technology teams to translate complex data into strategic recommendations, scalable decisioning solutions and measurable in-market outcomes.

As a team, we value curiosity, pragmatism, technical excellence and impact. We move quickly, work collaboratively and focus on using data, analytics and AI to improve how customers experience the bank every day.

As an Advanced Analytics Manager, you will use rich customer data, advanced analytical methods and commercial judgement to deliver actionable insights, optimise customer engagement strategies and support data-driven decisioning across high-growth ventures and propositions.

This is a hands-on advanced analytics role where you will frame ambiguous business problems, develop analytical approaches, design and optimise customer decisioning strategies, and translate complex findings into clear recommendations for senior stakeholders.

You will balance technical delivery with commercial thinking, helping shape how value is delivered to customers through analytics-led experimentation, optimisation and decisioning.

To achieve this, you may expect to:

• Partner with product, marketing, growth and technology teams to define analytical objectives, success measures and decisioning opportunities
• Analyse customer behaviour, campaign performance, journey effectiveness and portfolio outcomes to identify opportunities for growth, optimisation and improved customer experience
• Design, test and optimise Next Best Conversation strategies using customer data, segmentation, experimentation and decisioning logic
• Translate ambiguous business problems into measurable problem statements, structured analytics strategies, clear insights, and practical recommendations for senior stakeholders
• Use SQL, Python/R, dashboarding tools and, where relevant, RAG-enabled knowledge retrieval to wrangle complex data, connect structured analysis with internal knowledge, and turn raw information into reusable outputs, scalable reporting and decision-ready insights
• Work closely with the Senior Project Manager and Head of Growth to build an insights-led and analytics-driven culture across the team
• Maintain a strong focus on compliance, responsible data use and risk management, incorporating risk reduction into processes, recommendations and decisioning activity

As an individual contributor, you will be a highly skilled technical specialist who brings:

• Advanced SQL skills, with experience querying, joining and transforming large, complex customer datasets across multiple sources
• Strong Python and/or R capability, with experience using code to solve analytical problems beyond the limits of standard reporting, campaign or decisioning tools
• Demonstrated experience in customer decisioning, personalisation or Next Best Conversation / Next Best Action strategy design and optimisation
• Strong experience in campaign analytics, customer segmentation, propensity modelling, experimentation, performance measurement and optimisation
• Ability to translate business problems into analytical frameworks, including defining hypotheses, success metrics, test design and measurement approaches
• Experience working with customer journey, behavioural, digital, product and campaign performance data to identify opportunities and drive measurable outcomes
• Exposure to predictive modelling, machine learning, model outputs or decisioning logic in a customer engagement environment
• Exposure to AI-enabled analytics, RAG pipelines, agentic architecture or AI decisioning frameworks is preferred but not essential

Why CommBank

Be part of a high-impact analytics community where your work directly shapes customer experience and venture growth. We value curiosity, pragmatism and continuous learning, and support your career development every step of the way.