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. As a Senior Data Scientist within the team, you will independently review, challenge and validate AI use cases across the Group. You will assess whether AI systems are fit for purpose and operate as intended, and whether the risks they introduce are understood and appropriately controlled.
You will design and carry out validation that is proportionate to the risk, covering data, methodology, assumptions and outcomes, and explain your findings clearly to technical and non-technical stakeholders. Model approvals, usage decisions and risk acceptance will draw directly on your analysis and judgement.
You will work closely with model developers, product owners and business stakeholders, while remaining independent of them, and provide constructive challenge that supports safe and sustainable AI adoption. You will also help develop the team's AI validation practices, tooling and standards, sharing knowledge and building capability across the team.
A courageous mindset and a proven record of self-directed learning, with the curiosity and discipline to stay ahead of fast-changing AI techniques and risks
Close attention to detail and a knack for spotting problems
Working knowledge of GenAI and agentic architecture, including 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, including synthetic data generation. Experience in fine-tuning transformer models is also a plus.
Experience with current GenAI frameworks and tools like LangChain, OpenAI Agents SDK, LangGraph, Pydantic, Langfuse/HoneyHive or similar platforms.
Advanced Python, plus strong experience with GitHub, version control and CI/CD pipelines. SQL, R or TypeScript is a plus.
Comfort reading and navigating unfamiliar codebases, reproducing evaluation pipelines, writing test harnesses and inspecting 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.
Strong communication skills, with the ability to explain complex technical concepts to mixed audiences.
Working with us:
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Skills Required
- Advanced Python experience
- Hands-on experience designing, building, and evaluating AI and Generative AI solutions
- Working knowledge of GenAI and agentic architectures, including orchestrators, sub-agents, RAG pipelines, tool use, guardrails, multi-agent routing, memory, persona handling, and LLM-as-a-Judge
- Experience with current GenAI frameworks and tools such as LangChain, OpenAI Agents SDK, LangGraph, Pydantic, Langfuse, or HoneyHive
- Strong experience with GitHub, version control, and CI/CD pipelines
- Experience reading unfamiliar codebases, reproducing evaluation pipelines, writing test harnesses, and inspecting trace data
- Hands-on experience with AI coding agents, including Claude Code and Codex
- Ability to build and maintain coding-agent skills, sub-agents, hooks, and plugins
- Working knowledge of traditional machine learning models, including regression, random forests, XGBoost, and related evaluation methods
- Strong communication skills with technical and non-technical audiences
- Proven self-directed learning, curiosity, discipline, and attention to detail
- Experience generating synthetic data
- Experience fine-tuning transformer models
- Experience with SQL, R, or TypeScript
Commonwealth Bank Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Commonwealth Bank and has not been reviewed or approved by Commonwealth Bank.
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Leave & Time Off Breadth — The bank offers additional Life Leave, the option to purchase up to four extra weeks, pet leave, and paid volunteering leave alongside flexible-working options. Public materials indicate these leave features compare well within Australian banking.
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Parental & Family Support — Permanent employees can access up to 18 weeks of paid parental leave, and superannuation is paid for up to 34 weeks of unpaid parental leave. These provisions extend support for new parents beyond standard settings.
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Wellbeing & Lifestyle Benefits — Access includes CBHS Health Fund, Fitness Passport, a 24/7 wellbeing platform with telehealth, an Employee Assistance Program, and employer‑paid income protection for up to two years, alongside staff banking perks and share plans. This combination provides day‑to‑day value across health, protection, and financial perks.
Commonwealth Bank Insights
What We Do
Australia’s leading provider of financial services including retail, premium, business and institutional banking, funds management, superannuation, insurance, investment and sharebroking products and services. We are a business with more than 800,000 shareholders and over 52,000 employees. We offer a full range of financial services to help all Australians build and manage their finances.
