Chapter Lead (Executive Manager) - Data Science and Gen AI, Model Risk Validation

Chapter Lead (Executive Manager) - Data Science and Gen AI, Model Risk Validation You’re passionate about leading high-performing teams and validating cutting-edge AI models  We’re transforming financial services through scalable and ethical AI innovation Together, we’ll deliver robust model validation frameworks that drive trust and impact Do Work That Matters   At CommBank, we’re redefining the future of banking through world-class AI innovation.

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 Chapter Lead (Executive Manager) in our AI & General Model Validation team, you’ll lead a talented group of data scientists across Australia and India, driving excellence in model validation and tooling development.

You’ll play a key role in shaping AI models at CommBank, ensuring our models are safe, scalable, and aligned with customer and regulatory expectations. You will represent the chapter with model developers, senior business leaders, product owners and governance experts. See Yourself in Our Team CommBank is leading new-to-the-world innovations. As part of our team, you’ll be empowered to shape the future of AI in financial services, working alongside top-tier talent in a collaborative, inclusive environment.

Model Risk & Validation is part of Risk Management and provides considered challenge to improve modelling outcomes. We’re seeking an exceptional AI Chapter Lead (Executive Manager) to shape the future of AI model validation at scale. You’ll be part of a collaborative, forward-thinking team committed to ethical AI, innovation, and continuous learning at scale. Your Impact:   Lead a chapter of data scientists across Australia and India, including hiring, coaching, performance and career development.

Occasional international travel may be required . Plan and run the chapter’s validation work, from prioritising engagements to delivering on time at a consistent quality bar. Lead the development of validation tooling and methods and stay close enough to the work to challenge methodology and evidence. Engage senior stakeholders, including General Managers, model owners, central AI teams and internal audit.

We are interested in people with:   Leadership & Vision: Proven experience in leading high-performing multidisciplinary teams with Gen AI, data science, and software engineering skill sets. Experience in mentoring data scientists and leading technical initiatives. Project management experience in agile environments. Enthusiastic about developing automation tools to drive continuous workflow improvements.

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   Strong stakeholder management skills. Exceptional communication skills and a growth mindset. Knowledge of model risk governance and validation processes is desirable. Technical Excellence: The ideal candidate will have depth across several of the areas above.

We do not expect mastery of every technology listed. Deep working knowledge of GenAI and agentic architectures with enough depth to challenge the design. 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   Practical experience with AI coding agents (including Claude Code, Codex and GitHub Copilot) and skills, sub-agents, hooks and plugins that automate validation or engineering workflows.

Working knowledge of traditional machine learning models, including random forests, XGBoost , and related evaluation meth