Level

Commonwealth Bank of Australia

Advanced Analytics Analyst - Card Fraud & Scams Analytics

AI in this role

Develop predictive and machine learning models to detect and prevent credit card fraud using advanced data analytics and generative AI tools.

databricksgithub
fraud-detectiondata-analysismachine-learninggenerative-aipython
  • Work with world class analytics teams, tools and technologies
  • Build practical solutions that serve and protect millions of Australians
  • Limitless learning in an agile, collaborative and innovation led environment

 


See Yourself in the Team

The Cards Fraud and Scams team are a dynamic and inclusive group of fraud specialists working together to detect, prevent and respond to fraud across credit, debit, prepaid, travel money and merchant products.

We use data-driven insights, advanced systemic rules, cloud technologies and AI tools to identify suspicious activity, understand emerging threats and help keep our customers and communities safe. Working in a 24/7 environment, we partner closely with fraud operations, risk specialists and stakeholders across the Group to respond to incidents, understand trends and proactively mitigate fraud risk.

You’ll be part of a team where curiosity is valued, new ideas are encouraged and there are opportunities to apply emerging technology to real-world problems.

 


Your Impact & Contribution

You’ll bring data, analytics and technology together to help solve complex fraud problems. In this role, you’ll analyse large and complex datasets to uncover fraud patterns, trends, emerging risks and opportunities to improve detection and prevention. To achieve this, you may expect to:


  • Develop and refine analytical, predictive and machine learning solutions that support fraud detection, risk assessment and operational decision-making.
  • Apply generative AI and AI-assisted development tools to explore new ways of solving problems, improving productivity and enhancing fraud capabilities.
  • Build practical analytics products, including dashboards, reporting and reusable analytical solutions that turn complex information into clear, actionable insights.
  • Partner closely with Fraud Operations and Risk teams to understand business problems, identify automation and optimisation opportunities and translate them into measurable analytical solutions.
  • Maintain high-quality, reusable analytical code and documentation, using GitHub or similar version-control practices to support sustainable development.
  • Communicate insights and recommendations clearly, tailoring your approach for technical specialists, fraud experts and non-technical stakeholders.
  • Stay curious and continuously learn, keeping pace with developments across analytics, machine learning, generative AI and cloud technologies and identifying opportunities to apply them to fraud challenges.

 


Your Skills & Experience

You’ll be a curious and analytical problem solver who enjoys working with data, learning new technologies and applying your skills to meaningful business problems. You’ll bring:

  • Commercial experience in data analytics, data science or a related quantitative discipline, with experience turning data into insights and practical solutions.
  • Strong SQL and Python or R capability, with experience working with large and complex datasets.
  • Experience with statistical analysis, predictive modelling or machine learning, and an interest in applying these techniques to real-world problems.
  • Exposure to generative AI or AI-assisted development tools, with a willingness to experiment and find practical applications for emerging technology.
  • Experience with version control, such as GitHub, and an appreciation for clean, reusable and well-documented analytical code.
  • Familiarity with modern cloud data platforms, such as AWS, Snowflake, Azure, Google Cloud or Databricks.
  • Strong problem-solving and communication skills, with the ability to translate complex analytical concepts into clear recommendations.
  • Sydney or Melbourne based considered.


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 this opportunity excites you, we’d love to hear from you. Apply now and help shape smarter ways to protect our customers and communities.

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: 09/10/2026

How we rate this

Advanced Analytics Analyst - Card Fraud & Scams Analytics at Commonwealth Bank of Australia rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Fraud DetectionData AnalysisMachine LearningGenerative AIPythonDatabricksGithub

Questions you could be asked

  1. Tell me about a project where fraud detection was part of your work. What did you do?
  2. Tell me about a project where data analysis was part of your work. What did you do?
  3. Tell me about a project where machine learning was part of your work. What did you do?
  4. Tell me about a project where generative ai was part of your work. What did you do?
  5. Tell me about a project where python was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Fraud Detection, Data Analysis, Machine Learning, Generative AI, and Python. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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