Data Scientist - Risk Management

• Apply your problem solving and critical thinking skills to assess model performance, compliance, and risks. 

• Validate machine learning, GenAI, and agentic models designed to address financial crime risk. 

• Work on transitioning legacy rule-based systems to modern ML approaches 

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 Data Scientist, AI & General Model Validation who applies deep technical expertise to ensure our models are robust, reliable, and ready for the future.  

See yourself in our team:

You’ll be part of a newly established model validation capability focused on financial crime modelling. This team is responsible for validating a pipeline of models transitioning from traditional rule-based alerting to machine learning-driven approaches.  

Working closely with stakeholders across Risk and Financial Crime, you’ll contribute to ensuring models are robust, compliant, and effective in identifying risk. The team operates in a highly collaborative environment and offers opportunities to work across different model types and use cases over time. 

About the role 

As a Data Scientist, you will contribute to the validation, development, and ongoing monitoring of machine learning models within the financial crime domain. 

In the near term, your work will focus on validating machine learning models replacing rule-based systems, with broader exposure to AI use cases as the capability evolves. 

Key responsibilities:

• Source, clean and prepare large, complex datasets for modelling and validation 

• Apply statistical and machine learning techniques to assess model performance and risk 

• Support validation of machine learning models used in financial crime detection 

• Collaborate with stakeholders to understand requirements and propose data-driven solutions 

• Contribute to model deployment, monitoring, and lifecycle management processes 

• Apply software engineering practices across development and validation workflows 

We’re interested in hearing from people who have:

• Experience as a Data Scientist with strong foundations in Statistics, Mathematics, Data Science and GenAI 

• Hands-on experience building or working with Machine Learning models 

• Strong capability in data preparation, analysis, and modelling techniques 

• Strong programming skills and experience with tools like Python, R, SQL, Spark, TensorFlow, and PyTorch; familiarity with version control (GitHub)  

• Understanding of model validation, risk, or governance is advantageous 

• Experience in financial crime, risk modelling, or regulated environments is highly regarded 

• Experience with platforms like AWS SageMaker, AWS Bedrock, or H2O.ai is a plus.  

• Strong problem-solving skills and ability to communicate insights to stakeholders 

Why CommBank? 

CommBank is at the forefront of innovation in banking, embracing advanced analytics, machine learning and emerging AI capabilities to transform how we operate and serve our customers. 

You’ll be part of a growing capability shaping how financial crime is detected and managed, with opportunities to expand into broader AI use cases as the roadmap evolves. 

Working with us