Senior Analyst, Applied AI & Automation

About the role

The Fraud, Scams & Cyber Data, Analytics and AI team at CommBank protects customers and the Group from sophisticated threats by combining data, analytics and emerging AI. You will join the People Capability Automation team, reporting to the People Capability Automation Lead, which explores how analytics, AI and intelligent automation can transform manual processes. The role starts with Quality Assurance, working with Fraud Analytics, Operations, Technology, Risk and AI specialists to analyse customer interactions and operational data.

Key responsibilities

• Design and build agentic AI solutions that automate parts of the fraud and scams quality assurance lifecycle.
• Explore where LLMs, agents and intelligent automation can replace or augment manual QA processes.
• Develop and orchestrate multi-step AI workflows that reason across unstructured information, interact with data and tools and coordinate tasks.
• Use SQL and Python to explore, prepare and analyse customer, interaction, case and operational data.
• Apply NLP, classification, predictive analytics and machine learning where appropriate.
• Prototype and evaluate new approaches, then build scalable, reusable solutions.
• Design testing and evaluation frameworks to measure performance, identify failure modes and reduce hallucinations.
• Partner with Fraud Analytics, Quality Assurance, Product, Technology and Risk teams to turn ideas into practical, scalable solutions.

Required profile

• Hands-on analytics capability with SQL and Python, extracting, preparing and interpreting complex structured and unstructured datasets.
• Experience applying classification, predictive analytics, statistical modelling or machine learning to real problems.
• Practical experience building solutions with Generative AI and LLMs, beyond just using AI tools.
• Experience designing agentic or multi-step AI workflows, including orchestration, reasoning, retrieval and tool use.
• Understanding of AI evaluation and reliability, including testing model and agent behaviour and reducing hallucinations.
• Experience in fraud, scams, financial crime, quality assurance, risk, compliance or controls testing is beneficial.

Required skills

• SQL and Python
• NLP, classification, predictive analytics and machine learning
• Generative AI and LLMs
• Agentic frameworks such as Copilot Studio, LangGraph, LangChain, Semantic Kernel or AutoGen (highly valuable)
• Git/version control, APIs and collaborative or AI-assisted development environments