Business & Team
Financial Crime AI Team, COO
Overview
At the heart of the Chief Operations Office, we're driving CBA's ambition to detect, deter and ultimately eliminate financial crime through the power of transformative AI solutions.
As a Principal Data Scientist in Financial Crime domain, you'll be a hands‐on technical leader working in cross‐functional squads with engineers and other experts to design and deliver innovative, responsible and high‐impact AI solutions. You'll stay at the forefront of emerging technologies, fostering a culture of curiosity, inclusion, and continuous learning in the team, and translating complex ideas into high‐impact outcomes for our customers and colleagues. You'll contribute strongly to guide the team on technically demanding problems across Fin Crime domain as AI continues to evolve.
Key Responsibilities
* Lead GenAI and Agentic system design and development: Prototype, design, develop, deploy and design monitoring for innovative GenAI and Agentic solutions that transform the prevention, detection and investigation of Financial Crime in the bank while setting technical direction and best practices across the domain.
* Develop and implement Machine Learning Models: Prototype, design, build, deploy and monitor a variety of machine learning models.
* Expand Data/AI Science Usage: Identify potential AI opportunities across Fin Crime for future focus.
* Drive Continuous Improvement and Business Outcomes: Work closely with financial crime stakeholders to understand risk and operational pain points, driving adoption of AI and GenAI to enhance detection, improve investigative outcomes, and shape the future operating model.
Technical Leadership and Coordination
* Ability to coordinate effectively across the Fin Crime and COO Data Science community to unify efforts and drive collaborative outcomes.
* Demonstrated capability in driving outcomes that are reusable and can be leveraged across the group.
* Intellectual curiosity and ability and willingness to learn, experiment and lead new to the world concepts.
Technical Skills and Tools
* Generative AI: Experience designing and deploying various aspects of Generative AI, including prompt engineering, Retrieval‐Augmented Generation (RAG), guardrail design, orchestration design, skills, evals frameworks, and tools such as LangChain and LangGraph.
* Machine Learning: Expertise in the design and construction of machine learning models, including natural language processing, unsupervised clustering and classification algorithms including feature engineering, model selection, hyperparameter tuning, model evaluation, and deployment of models into production environments.
* Cutting‐Edge AI: Work on projects leveraging traditional AI, Generative AI, and agentic AI to pave the path for how banking and broader industry functions in the future.
* Version Control and CI/CD: Experience with version control and CI/CD pipelines such as GitHub.
* Tooling: Hands‐on experience with data science tools such as Spark, Python, R, TensorFlow, PyTorch, and SQL.
* Data Engineering: Knowledge of ETL processes and data pipeline construction, ensuring efficient data flow and integration.
* Deployment: Familiar with Docker for containerization and deployment of applications.
* Cloud Architecture: Grounded understanding in AWS or Azure Cloud architecture and integration, demonstrating experience in deploying and managing cloud‐based solutions.
Working with Us
Our people bring their diverse backgrounds and unique perspectives to build a respectful, inclusive, and flexible workplace with an ultimate flexibility to work from any of our engineering hubs within Australia. 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.
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