Card Merchant Fraud Analytics Manager

Requirements

• Strong analytical engineering capability: rule logic, statistical reasoning, and problem‑solving in fast‑moving environments.
• Strong coding capability in SQL and Python (SAS experience beneficial; ability to learn new languages valued).
• Proven stakeholder management and influencing skills - regular engagement required.
• Experience working with or migrating to cloud data/analytics platforms (AWS/Snowflake exposure advantageous).
• Fraud/scams domain experience beneficial, but strong analytics experience can be sufficient with learning agility.
• Why Join Us
• At CommBank, you'll be part of a team that:
• Puts customers at the centre of everything we do
• Uses data, analytics and technology to solve meaningful problems
• Values continuous improvement, collaboration, and strong risk culture
• Supports flexible ways of working and career growth
• 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: 01/07/2026

Benefits

Additional Information

Flexible working, hybrid environment, and central offices Inclusive team where diverse perspectives are valued Access to world-class learning, technology tools and analytics teams See Yourself in the Team Fraud Analytics within the Chief Operations Office Data AI Analytics - Fraud CoE are responsible for developing, maintaining and enhancing the fraud detection systems, algorithms and reporting engines across CommBank and Bankwest, strengthening detection capability through intelligent automation, emerging trend analysis, advanced modelling and stakeholder reporting. In practice, the team sit at the heart of day-to-day fraud and scams defence, maintaining and evolving the fraud rule detection suite, creating new detection logic at pace, and partnering closely with stakeholders as products, channels and customer behaviours change. Our work is customer-critical. We balance strong fraud and scams protection with the need to minimise friction for genuine customers, using intelligent automation, emerging trend analysis, advanced modelling and stakeholder reporting to strengthen detection capability. The team are also evolving towards leveraging modern analytics platforms, and creating opportunities to influence how fraud analytics is delivered into the future. Your Impact & Contribution As an Advanced Analytics Manager in Fraud Analytics, you will lead the development and uplift of fraud detection strategies across assigned portfolios by owning complex analytics solutions, rule logic, and stakeholder outcomes. You'll play a key role in enhancing the fraud rule detection suite used to detect, prevent and disrupt fraudulent and scam activity, including decisioning outcomes such as holds, declines, alerts and customer push notifications. This is an Individual Contributor role where you may expect to: Lead the delivery of high‑impact enhancements to the fraud rule detection suite, including rule design, optimisation and quality controls. Translate fraud/scam trends and incidents into detection strategy changes delivered at pace. Partner with product/channel stakeholders to onboard new signals and data points required for detection (e.g., feature changes that introduce new fraud vectors). Own stakeholder reporting rhythms (weekly/monthly), ensuring insights are actionable and decision‑ready. Provide technical leadership across tooling evolution Champion continuous improvement: reduce false positives, manage alert volumes and minimise friction for genuine customers.

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