Senior Data Scientist, ML, NLP, GenAI, Agentic AI

Commonwealth Bank of Australia is hiring a Senior Data Scientist, ML, NLP, GenAI, Agentic 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.
Tools and skills the posting cites include RAG, AI agents and MLOps.
Level classifies it as a senior role.
Level lists 201 other open roles at Commonwealth Bank of Australia.

AI in this role

ragai-agentsml-opsnlpai-safety

Shape the future of customer experiences through Machine Learning, NLP, GenAI and Agentic AI

Drive innovative AI solutions that transform customer and adviser experiences across SMSF and Wealth Crew.
Lead end-to-end delivery at scale of GenAI and Agentic AI solutions, alongside machine learning and Natural Language Processing (NLP) models.
Influence AI strategy, governance and responsible-AI practices across Wealth & Private Banking.

At CommBank, we're investing in modern, future-ready data and AI capabilities. This is an opportunity to join our SMSF (Self-Managed Super Funds) Squad within Wealth & Private Banking and help build intelligent, customer-centric solutions that deliver real value for customers, colleagues and communities.

Do work that matters

As a Senior Data Scientist, you'll be a hands-on technical leader building an intelligent assistant that raises the standard of customer service for SMSF customers and advisers in the Mass Affluent segment of Wealth & Private Banking. You'll design, build and productionise the customer-centric models and agentic workflows behind it, partnering with product, technology and business stakeholders to identify where AI can lift service quality, resolve customer needs faster and unlock new insights.

You'll move AI initiatives from experimentation into production, taking ownership from first prototype through to a reliable, monitored service.

See yourself in our team

The SMSF and Wealth Crew is focused on customer service excellence: delivering customer-centric, data-driven solutions that enhance customer outcomes and improve the way customers interact with our Wealth and Private Banking services.

You will:

Design, build and productionise GenAI and Agentic AI solutions.
Apply Large Language Models (LLMs), retrieval-augmented generation (RAG) and agentic workflows to solve complex business challenges.
Build evaluation harnesses, guardrails and adversarial safety testing for non-deterministic GenAI and agentic systems.
Build and productionise models using modern MLOps practices and AI tooling.
Translate complex business problems into practical AI and machine learning solutions.
Drive best practice across model governance, monitoring, explainability and responsible AI.
Set technical direction and lift the squad's AI capability through mentoring and design and code review.
Partner with senior stakeholders and clearly communicate technical recommendations and trade-offs.
Influence strategic discussions around data quality, governance, data risk and AI adoption.

We're interested in hearing from people who have:

Strong experience designing, developing and deploying machine learning solutions in production environments.
Deep expertise in Natural Language Processing (NLP), Large Language Models (LLMs) and GenAI applications.
Experience developing Agentic AI solutions, AI assistants, autonomous workflows or coding agents.
Experience evaluating and hardening LLM or agentic systems: eval frameworks, LLM-as-judge, guardrails, hallucination and safety testing.
Hands-on programming experience with Python and SQL.
Experience with MLOps, CI/CD, model deployment, monitoring and observability frameworks.
Strong understanding of data governance, data quality, data risk and responsible AI principles.
The ability to influence stakeholders and communicate complex technical concepts to non-technical audiences.
A curious mindset and a genuine passion for customer service excellence, solving real customer problems through data and AI.

Experience within financial services, wealth management or superannuation is advantageous but not essential.

Working with us

At CommBank, we're committed to creating an accessible, inclusive and respectful workplace. We welcome applications from people of all backgrounds and are particularly committed to making a positive difference for Aboriginal and Torres Strait Islander Peoples.

Bring your ambition and we'll help you grow, belong and shape what's next through cutting-edge AI, modern data platforms and meaningful customer impact.

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: 11/11/2026

How we rate this

Senior Data Scientist, ML, NLP, GenAI, Agentic AI at Commonwealth Bank of Australia rates 87 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.

Classification

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.

Key facts

Senior Data Scientist, ML, NLP, GenAI, Agentic AI is an open job at Commonwealth Bank of Australia.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Sydney CBD Area.
The job was posted on September 23, 2026.
Seniority: senior.
Applications are handled by Commonwealth Bank of Australia. Apply on Commonwealth Bank of Australia

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsML OpsNLPAI Safety

Also common in data scientist jobs at this level

AWS Spark PyTorch Deep learning TensorFlow scikit-learn

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 monitor a model once it's live, and how do you know it needs retraining?
What NLP problem have you worked on, and how did you measure whether it actually worked?
How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

List these exact terms on your resume: RAG, AI agents, ML Ops, NLP, 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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