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Über diese Chapter Lead AI Stelle bei Commonwealth Bank of Australia

Commonwealth Bank of Australia · Vor Ort · Sydney CBD Area
  • Lead the design and delivery of advanced machine learning, Generative AI and agentic AI solutions for home buying.
  • Solve complex credit-modelling challenges and influence high-priority initiatives across Retail Banking Services.
  • Work with modern data science, cloud and engineering technologies to help shape the future of banking through responsible AI.

Grow. Belong. Shape what’s next.


Do work that matters.

At CommBank, we have an ambitious goal to lead the way in how artificial intelligence transforms banking. With strong support from our senior leadership, we are investing in AI capabilities that can deliver better experiences for our customers and create meaningful value for the communities we serve.

Reporting to the Chapter Area Lead, Home Buying, you will provide technical leadership and deliver high-priority AI and machine learning initiatives across Retail Banking Services.

This role combines deep machine learning expertise, statistical rigour and structured problem solving with the opportunity to apply Generative AI and agentic AI. Your initial focus will include credit modelling for home buying, with the opportunity to expand the use of data science and AI across a broader range of banking challenges.


See yourself in our team.

Be part of the team at the heart of how CommBank serves Australia. Retail Banking Services supports more than 10 million personal and small business customers through market-leading products, services and digital experiences.

You will join a team focused on using data, machine learning and emerging AI technologies to solve complex problems and deliver better customer and business outcomes.

In this role, you will:

  • Lead the design, development and implementation of machine learning models that support strategic business and customer outcomes.
  • Apply statistical methods and structured problem solving to complex credit-modelling challenges within home buying.
  • Progress models from exploration and experimentation through validation, deployment and ongoing monitoring.
  • Design and develop Generative AI capabilities, including Retrieval-Augmented Generation, orchestration, guardrails and agentic AI systems.
  • Identify opportunities to expand the effective and responsible use of data science, machine learning and AI across Retail Banking Services.
  • Partner with product, engineering, risk and business stakeholders to define problems, evaluate trade-offs and translate technical insights into action.
  • Establish strong technical practices across feature engineering, model selection, evaluation, documentation and production deployment.
  • Contribute to the ongoing development of AI and machine learning capability through knowledge sharing, technical guidance and collaboration.

We’re interested in hearing from people who:

You are an experienced data science or machine learning practitioner who enjoys solving complex problems and turning emerging technologies into practical outcomes. You combine strong technical judgement with the ability to communicate clearly and build trusted stakeholder relationships.


You will bring:

  • A strong foundation in statistics, probability and machine learning, including the ability to interpret, evaluate and explain model behaviour.
  • Advanced Python capability and substantial experience designing, developing and deploying machine learning models.
  • Experience with Generative AI, large language models or conversational AI, including prompt engineering, Retrieval-Augmented Generation, orchestration or guardrail design.
  • Experience developing production solutions using relevant technologies such as Spark, SQL, TensorFlow, PyTorch or R.
  • An understanding of data engineering, ETL processes, data pipelines, version control and continuous integration and delivery practices.
  • Experience with cloud-based environments such as AWS or Azure, and familiarity with containerisation technologies such as Docker.
  • Strong written and verbal communication skills, with the ability to document technical work and engage stakeholders from technical and non-technical backgrounds.
  • A tertiary qualification in Data Science, Statistics, Computer Science or a related discipline.

If you’re motivated by the opportunity to combine rigorous machine learning with the possibilities of Generative and agentic AI, we’d love to hear from you. Apply today.


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.

If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career.

We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696.

Advertising End Date: 18/11/2026
Bereit, sich bei Commonwealth Bank of Australia zu bewerben?
Bei Commonwealth Bank of Australia bewerben

Über Commonwealth Bank of Australia

Whether you’re passionate about customer service, driven by data, or called by creativity, a career with CommBank is for you. Our people bring their diverse backgrounds and unique perspectives to build a respectful, inclusive and flexible workplace. One where we’re driven by our values, and supported to share ideas, initiatives, and energy. One where making a positive impact for customers, communities and each other is part of our every day. Here, you’ll thrive. You’ll be supported when faced with challenges, and empowered to tackle new opportunities. We really love working here, and we think you will too.

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