About the Role
As a Data Scientist in the Marketing & Corporate Affairs (MCA) Data Science team, you will design, build and high‐produce data‐science and AI solutions that shape how Commonwealth Bank understands and serves customers at scale.
You will contribute across the full AI lifecycle – from problem definition and experimentation through to deployment, monitoring and continuous improvement. Your work will directly inform decision‐making across marketing, customer experience and communications.
From applying Generative AI to unlock insight from unstructured customer data to designing agent‐oriented AI patterns that automate analysis and decision workflows, you will work on high‐impact, applied use cases at the forefront of modern data science.
Key Responsibilities
* Partner closely with stakeholders across Marketing & Corporate Affairs, working alongside product managers, analysts, engineers and risk teams to co‐create practical, outcome‐focused solutions.
* Help apply AI and data science to improve customer outcomes, optimise journeys and deliver measurable commercial and risk benefits.
* Contribute to the broader CBA Data Science Practice, supporting shared standards, governance and capability uplift.
* Maintain production readiness, including deployment, monitoring and continuous improvement of AI solutions.
What We're Looking For
* Build production‐ready data science and Generative AI solutions with real‐world impact.
* Enjoy working with open‐ended problems and turning complex data into clear insights and actions.
* Combine classical data science, machine learning and GenAI approaches to deliver business value.
* Work collaboratively and confidently with senior stakeholders to shape and refine use cases.
* Motivated to learn and contribute to scalable, governed AI systems in a regulated environment.
* Balance creativity with thoughtful consideration of risk, ethics and safety.
Technical Skills & Experience
* Experience applying Generative AI concepts or building prototype GenAI applications.
* Hands‐on use of Large Language Models (LLMs) for analytics, insight generation or decision support.
* Exposure to agentic or multi‐agent GenAI frameworks (such as Semantic Kernel, AutoGen, LangGraph or similar).
* Strong foundations in data science and AI, including prompt engineering, retrieval‐augmented generation (RAG), evaluation and safety guardrails.
* Experience, or a strong interest, in developing and deploying models on cloud platforms (for example, AWS).
* Solid grounding in statistics, modelling, experimentation and data wrangling.
* Strong communication skills, with the ability to explain technical concepts to non‐technical and senior audiences.
* A tertiary qualification in Statistics, Mathematics, Computer Science or a related discipline.
Advertising End Date: 17/05/2026
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