Principal Data Scientist – Financial Crime Model Validation 

• ​Lead a new financial crime model validation capability and help shape how modern machine learning and AI is adopted in a highly regulated environment. 

• Join a team building dedicated expertise to support the move from rule-based alerting to machine learning/GenAI-based model validation. 

• Grow your impact with a bank investing in data science, model governance and AI-enabled tooling across the model lifecycle. 

Do Work That Matters 
At CommBank, Data Science is evolving quickly, with stronger tooling, reusable assets and AI-enabled support helping teams move from experimentation to production with greater speed, rigour and impact. In this role, you’ll help build a new capability within the model validation team dedicated to financial crime models, supporting a critical transition from traditional rule-based alerting to modern machine learning approaches. 

See yourself in our team 
You’ll join a model validation team where a new capability is being established to support incoming financial crime model validation work. This team’s work sits at the intersection of data science, governance, financial crime risk and technology, and offers the chance to work on high-priority use cases as the bank moves from traditional rule-based alerting to modern machine learning and AI-driven approaches. 

You’ll help shape how advanced analytics, ML, GenAI and agentic AI-enabled ways of working are adopted responsibly in a highly regulated environment, while building broader exposure across other model domains over time. 

• Lead the financial crime model validation stream across a newly created capability, helping shape how the work is planned and delivered. 

• Validate machine learning models designed to replace legacy rule-based financial crime alerting approaches. 

• Provide technical leadership on model design, statistical methods, machine learning and GenAI approaches in a regulated environment. 

• Support computationally intensive financial crime use cases, including models that scan high volumes of transaction data over extended time periods to generate customer-level features. 

• Guide stakeholders through model risk, governance and validation requirements in a way that is practical and commercially aware. 

• Work closely with stakeholders to solve complex problems, negotiate priorities and support delivery from end to end. 

• Contribute hands-on technical expertise while remaining an individual contributor rather than a formal people manager. 

• Help uplift capability within the team by mentoring others through project delivery and model validation practice. 

• Work in a Python, PySpark and AWS data science environment, with growing exposure to AI-enabled ways of working across the data science lifecycle. 

We’re interested in hearing from people who: 
You bring deep technical credibility, sound judgement and the confidence to lead complex validation work in a highly regulated domain. You’ll be at your best in this role if you combine strong machine learning foundations with experience in financial crime, model risk or model validation, and enjoy partnering with stakeholders to solve important problems well. 

• Experience in financial crime models, ideally from either a model validation or model development background. 

• Strong knowledge of statistics, machine learning and data science, including the ability to assess how models are built and whether they are fit for purpose. 

• Experience leading complex project work end to end, without needing formal line management responsibility. 

• A strong risk and governance mindset, particularly in regulated or assurance-heavy environments. 

• Confidence working with senior stakeholders and navigating competing priorities with sound judgement. 

• Strong hands-on technical capability in Python, PySpark and AWS, with experience building scalable data pipelines and engineering features from high-volume datasets. 

• The ability to coach and mentor others through technical delivery and validation challenges. 

• Curiosity to broaden into adjacent model domains over time as the team rotates talent across use cases. 

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.