Commonwealth Bank of Australia
Senior Data Scientist
Commonwealth Bank of Australia is hiring a Senior Data Scientist. Level rates it ; you can apply on Commonwealth Bank of Australia.
Level's read on this job
- On Level's scale, this data scientist role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include LangChain, LangGraph and PyTorch.
- Level classifies it as a senior role.
- Level lists 192 other open roles at Commonwealth Bank of Australia.
- The role was posted in the last few days.
AI in this role
See yourself in our team:
At CBA we have an ambitious goal of leading the way in changing the world through AI. With great buy-in from all senior leadership, we have embarked on world first initiatives to deliver exceptional experiences to our customers. In Retail Banking Services (RBS), as the largest and customer facing part of the bank, we play a unique role in bringing this vision to life and build a brighter future for all Australians.
The opportunity:
Reporting to the AI Domain Lead, you will deliver high priority initiatives across RBS. You will work on the delivery of world-class AI capabilities across RBS that will also build capabilities for the rest of CBA. You will be responsible for cutting edge initiatives in Agentic AI, GenAI, and broader AI. Our strategic focus lies in delighting our customers at every touchpoint, offering outstanding service, and meet the needs of our customers.
Why CommBank?
CommBank is leading the world of banking by venturing into new-to-the-world innovations. We're on the cutting edge, embracing AI technologies to reshape how we operate and serve our customers.
Key Responsibilities:
- GenAI and Agentic system design and development: Drive the expansion and adoption of Generative AI solutions across RBS, optimising our product offerings through design and implementation of advanced Gen AI capabilities and agentic AI systems.
- Develop and implement Machine Learning Models: Lead the overhaul of various machine learning models, enabling to drive strategic business outcome for various stakeholders.
- Expand Data/AI Science Usage: Identify AI opportunities and embed these methodologies into a broader range of activities across the banking landscape
- Drive Continuous Improvement and Business Outcomes: work closely with business stakeholder to pioneer adoption and application of cutting edge AI and Gen AI capabilities and paving the path for how the bank will operate to towards the vision of re-imagined banking and customer service.
We’re interested in hearing from people with the following skills:
- Proven experience in Gen AI, chatbot development, and LLMs.
- Strong foundation in statistics and probability; able to interpret models.
- Proficiency in Python and experience with AI/ML model development.
- Excellent communication skills for documentation and stakeholder engagement.
- Tertiary qualification in Data Science, Statistics, Computer Science, or a related field.
Technical Skills and Tools:
We use a broad range of tools, languages, and frameworks. We don’t expect you to know them all but experience or exposure with some of these (or equivalents) will set you up for success in this team.
- 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.
- Agentic AI: Experience designing and building autonomous or semi-autonomous agent systems — including intent/task orchestration, tool use, multi-step decision-making, and guardrails — using frameworks such as LangGraph, pydantic_ai, or equivalents.
- Generative AI: Familiarity with various aspects of Generative AI, including prompt engineering, Retrieval-Augmented Generation (RAG), guardrail design, orchestration design, and tools such as LangChain and LangGraph.
- · Machine Learning: Expertise in the design and construction of machine learning models, including feature engineering, model selection, hyperparameter tuning, model evaluation, and deployment of predictive models into production environments.
- 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:
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
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: 12/11/2026How we rate this
Senior Data Scientist at Commonwealth Bank of Australia rates 92 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
- $165k
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 do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide that one model's output is better than another's for a given task?
- What's a project where you used LangChain hands-on?
- Walk me through how you've used LangGraph in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI Evaluation, LangChain, and LangGraph. 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.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. You get your review by email within 24 hours.
Get new data scientist jobs (Builds AI ●●●●) by email
One email a week with the new data scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step