**You are**passionate about models and like to offer different angles on how to solve business problems with data
- **We are**a high performing team with a passion for innovation and continuous improvement
- **Together we can**deliver an exemplary experience for our stakeholders and the Group
**Do work that matters**
You will be part of a skilled quantitative team serving all business units across the CBA Group. Reporting to the Chapter Lead, Managerial Model Validation, Model Risk & Validation, your key responsibilities include:
**Leading validations for medium rated general models**:
- Formulating validation plans around how to assess and review a given model to ensure it is fit-for-purpose
- Allocation of validation tasks and escalation of blockers in a timely manner
- Solving complex modelling and validation problems independently
**Supporting a strategic transformation agenda**:
- Promoting and championing modern analytics tooling such as technical report writing use Quarto or R-Markdown
- Presenting to internal working groups, technical forums, governance committees and/or regulatory meetings
- Maintaining productive relationships with model development teams, model owners, business unit teams and other stakeholders
**See yourself in our team**:
Model Risk & Validation provides assurance and oversight of models across the group. The team leads and conducts validation of the Group's models, based on internal policy and procedures, regulatory guidance, and the industry's best practices.
It provides line 2 assurance and challenge for all models within the CBA group. The team also influences the technology, data and validation strategies through active engagement with BU's and executive level stakeholders across the group.
**We're interested in hearing from people who have**:
- Led in technical projects such as model developments and/or validations
- 4+ years of experience in building and/or validating models (inc. AI and Gen-AI), preferably in financial services; ability to pick up new concepts and modelling techniques quickly is essential
- Excellent written and verbal communication skills
- Tertiary qualifications, in a quantitative discipline such as statistics, data science, computer science, actuarial science, or software development
- Experience in developing/validating AI/ML models and tools using LLMs, Random Forests, Gradient Boosted Machines, Deep Neural Networks, etc.
- Advanced knowledge of modern analytical tools including R, Python or TypeScript. Knowledge in other programming languages such as SQL, C++, VBA, etc. is also desirable.
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Advertising End Date: 11/02/2025