Do Work That Matters:Are you ready to shape the future of model risk management in one of Australia's leading financial institutions?
At CommBank, we're looking for a Model Validation Lead (Senior Data Scientist) who blends deep technical expertise with strategic leadership to ensure our models are robust, reliable, and ready for the future.See yourself in our team:As a key member of our Model Risk & Validation team, you'll drive rigorous validation processes, deploy cutting-edge analytics tools, and embed robust risk management practices across our model ecosystem.
You'll lead a high-performing quantitative team, guiding them to uphold the integrity of our risk assessment framework while influencing the Group's broader AI and transformation strategies.Your core responsibilities will include:Model Validation & Technical Leadership - Design and execute comprehensive validation plans to assess model performance, compliance, and risk.Innovation & Continuous Improvement - Develop and integrate AI-driven tools to enhance validation quality and speed.Strategic Transformation & Stakeholder Engagement - Embed modern AI and risk frameworks into business strategies whilst building strong relationships with model developers, business units, to ensure transparency and alignment.Team Leadership & Mentorship - Mentor and guide team members, fostering a collaborative and inclusive culture and champion modern analytics tooling and promote best practices in technical communication.We are interested in hearing from people who have:Please note that we are interested in hearing from people who might not meet all the following criteria.
We're open to working with the right candidate to fill any skill gaps during your journey at CommBank.Degree qualified in Statistics, Data Science, Computer Science, Actuarial Science, or a related field—or equivalent industry experience.Hands-on experience in ML, Generative AI, Statistical Modeling, and Risk AnalyticsStrong programming skills and experience with tools like Python, R, SQL, Spark, TensorFlow, and PyTorch.Expertise in ML model development and evaluation, including GenAI techniques like RAG, prompt engineering, and orchestration tools (e.g., LangChain, LangGraph).
Familiarity with version control (GitHub), CI/CD pipelines, and data engineering practices.Experience with platforms like AWS SageMaker, AWS Bedrock, or H2O.ai is a plus.Excellent communication skills, with the ability to translate complex technical concepts for diverse audiences.Why Join Us?
At CBA, our Model Risk & Validation team plays a critical role in safeguarding the integrity of data-driven decisions across the Group.
We provide second-line assurance through rigorous oversight and challenge, ensuring every model meets internal and regulatory standards.
Join us and be part of a team that's shaping the future of risk, technology, and AI across the