Commonwealth Bank of Australia
Data Scientist, Gen AI
Commonwealth Bank of Australia is hiring a Data Scientist, Gen AI. Level rates it ; you can apply on Commonwealth Bank of Australia.
Level's read on this job
- Level rates this data scientist role Builds AI ●●●●: the job is building AI systems.
- The posting mentions RAG, AI agents and AI safety among its tools and skills.
- Commonwealth Bank of Australia has 213 other open roles on Level.
- Posted in the last few days.
AI in this role
Data Scientist, Gen AI
- Build production-ready generative and agentic AI solutions that improve customer experiences
- Solve complex technical challenges using modern AI models, retrieval systems and evaluation methods
- Help shape the safe, responsible and scalable use of AI across CommBank
Do Work That Matters
Join Retail Banking Services, the team at the heart of how CommBank serves Australia. The business supports more than 10 million personal and small business customers through market-leading products, services and digital experiences. You’ll help create solutions that positively affect customers’ lives while contributing to the future of digital banking.
As a Data Scientist in RBS Customer Digital and AI, you’ll build, validate and deploy generative AI and agentic AI solutions across our digital and assisted channels. Your work will improve customer experiences and commercial outcomes while strengthening the engineering and modelling standards that enable safe, explainable and production-quality AI.
You’ll join at an exciting point in CommBank’s technology journey. The Group is focused on adopting agentic and generative AI at scale, supported by secure foundations, responsible AI controls and collaboration between people and AI agents.
See yourself in our team
In this role, you will:
- Build and evaluate generative AI solutions, including retrieval-augmented generation, conversational assistants and colleague drafting tools
- Design agentic workflows that plan, use approved tools and complete multi-step tasks with appropriate permissions and human oversight
- Engineer prompts, system instructions and retrieval pipelines to improve grounding and response quality
- Create evaluation harnesses and golden datasets covering groundedness, accuracy, task completion, latency and cost
- Select and tune models for different use cases, balancing quality, cost, latency and data-residency requirements
- Apply responsible AI controls, including hallucination mitigation, prompt-injection testing, personal-information handling and risk-review evidence
- Work with engineering colleagues to deploy and monitor solutions, including guardrails, telemetry and drift detection
You’ll work across the model lifecycle, moving ideas from experimentation into production with rigour and measurable impact. CommBank’s Data Science Practice supports this through AI-enabled tools and reusable assets spanning feature engineering, model development, validation, monitoring and responsible AI guardrails.
We’re interested in hearing from people who:
Bring hands-on data science expertise and enjoy turning emerging AI capabilities into reliable solutions. You’ll be comfortable combining deep technical work with clear communication, sound judgement and collaboration across engineering, product, design and governance teams.
You will have:
- A tertiary qualification in data science, statistics, computer science, engineering or another quantitative discipline, or equivalent demonstrated experience
- Strong Python and SQL skills
- Practical experience with large language model and agent frameworks, vector stores and cloud AI platforms
- Experience in prompt and context engineering, retrieval design and the systematic evaluation of non-deterministic systems
- Experience delivering generative AI or machine-learning solutions into production, ideally within a regulated environment
- Knowledge of responsible AI, privacy and model-risk controls, including safety testing and guardrails
- The ability to explain model behaviour, limitations and risks to technical, non-technical and governance audiences
- Experience working in agile, cross-functional teams with engineers, product owners and designers
Bring your curiosity and technical ambition to help shape what responsible, customer-focused AI can achieve.
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 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: 04/12/2026How we rate this
Data Scientist, Gen AI at Commonwealth Bank of Australia rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $168k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you think about the risk of an AI system in this kind of role failing silently?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, and AI Safety. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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