Principal Data Scientist

Commonwealth Bank Of Australia; Sydney; On-site; AUD 180,000 - 240,000; Full time

Job summary

Commonwealth Bank of Australia in Sydney CBD, NSW, AU is seeking a Principal Data Scientist to lead validation of ML, AI models and GenAI systems. You will assess fit-for-purpose operation, drive risk opinions with governance stakeholders, and mentor a team of data scientists.

The role requires hands-on experience with PyTorch, SageMaker, and GenAI tooling, plus strong Python and GitHub CI/CD skills for building robust evaluation pipelines.

Qualifications

• Extensive experience in developing, evaluating or validating ML/AI, GenAI or statistical models.
• Independent judgement and ability to challenge stakeholders.
• Hands-on experience with AI solutions and model evaluation.
• Deep knowledge of GenAI and agentic architecture.
• Ability to lead data scientists through complex validation tasks.

Responsibilities

• Scope and design validation of complex ML/AI systems and lead the validation plan.
• Provide independent risk opinions to senior stakeholders.
• Set and improve AI validation practices, tooling and standards; mentor others.
• Lead other data scientists through validation work.

Skills

ML/AI validation

GenAI architecture

Python

GitHub CI/CD

Communication

Technical lead

SQL

PyTorch

AWS SageMaker

Education

Statistics/Data Science/CS/Actuarial

Degree in related field

Tools

LangChain

LangGraph

OpenAI Agents SDK

Pydantic

Langfuse/HoneyHive

Claude Code

Codex

Job description

Principal Data Scientist Commonwealth Bank of Australia Sydney CBD, NSW, AU

Do Work That Matters

AI & General Model Validation (AIGMV) provides independent technical challenge and review of the Group's most important ML and AI models, across business and support units.

See yourself in our team

As a Principal Data Scientist within the team, you will lead independent review, challenge and validation of ML, statistical and AI models across the Group, including GenAI and agentic systems. You will assess whether they are fit for purpose and operate as intended, and whether the risks they introduce are understood and appropriately controlled. This will involve:

Scope and design validation of complex ML and AI systems, split the work into a structured plan, and lead other data scientists through it

Form independent risk opinions and provide credible challenge to senior business, engineering and governance stakeholders

Set and improve the team's AI validation practices, tooling and standards, and mentor other data scientists

We’re interested in hearing from people who:

Extensive experience in developing, evaluating or validating ML/AI, GenAI or statistical models, or equivalent depth

A courageous mindset and independent judgement. You enjoy self-directed learning, and have the curiosity and discipline to stay ahead of fast-changing AI techniques and risks

Close attention to detail, and the judgement to see which problems matter

Deep working knowledge of GenAI and agentic architecture, enough to validate and challenge orchestrators, sub-agents, RAG pipelines, tool use, guardrails, multi-agent routing, memory and persona handling, and LLM-as-a-Judge

Hands-on experience designing, building and evaluating AI and Generative AI solutions. Fine-tuning transformer models is a plus.

Advanced Python, with strong GitHub, version control and CI/CD experience. SQL, R or TypeScript is a plus.

Ability to read and navigate unfamiliar codebases, reproduce evaluation pipelines, write test harnesses and inspect trace data

Hands-on experience with AI coding agents, including Claude Code and Codex, and the ability to build and maintain skills, sub-agents, hooks and plugins that automate workflows.

Working knowledge of traditional machine learning models, including regression, random forests, XGBoost, and related evaluation methods, and the ability to validate and challenge them.

Demonstrated experience as the technical lead on projects, leading other data scientists through the work rather than as a people manager, including turning a complex system into a structured test plan

Strong communication skills, with the ability to explain complex technical concepts to mixed audiences, including senior stakeholders and governance forums.

Practical experience with PyTorch and AWS SageMaker, and with GenAI tooling such as LangChain, LangGraph, OpenAI Agents SDK, Pydantic and Langfuse/HoneyHive

Degree in Statistics, Data Science, Computer Science, Actuarial Science, or a related field, or equivalent industry experience

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.

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