Organization: At CommBank, we never lose sight of the role we play in delivering a brighter future for our customers and supporting our communities. Our focus is to help customers and communities move forward to progress. To make the right financial decisions and achieve their dreams, targets and aspirations.

Regardless of where you work within our organization, your initiative, talent, ideas and energy all contribute to the impact that we can make with our work. Together we can build tomorrow’s bank today.

Job Title: Data Scientist

Location: Bengaluru, India

Business and Team: Financial Crime AI Team, COO

At the heart of the Chief Operations Office, we’re driving CBA’s ambition to detect, deter, and ultimately eliminate Financial Crime through transformative AI solutions.

As a Data Scientist in the Financial Crime AI team, you’ll lead and collaborate with data scientists, ML engineers, software engineers, and domain experts to build scalable, high-impact AI solutions across AML, fraud, scams, and risk intelligence.

You’ll stay at the forefront of emerging AI technologies, helping shape innovative, responsible, and impactful solutions for the future of Financial Crime prevention.

Impact and Contribution:
CommBank is redefining the future of banking through AI, data, and innovation. We’re investing in modern technology, scalable platforms, and world-class talent to build smarter and safer customer experiences.

Within the Financial Crime AI team, you’ll work on meaningful problems at scale — leveraging AI, machine learning, and advanced analytics to help combat fraud, scams, and financial crime. You’ll have the opportunity to innovate, influence strategy, and deliver solutions with real customer impact.

Roles & Responsibilities:

• Develop and deploy AI/ML models for Financial Crime use cases including AML, fraud, scam detection, and risk intelligence
• Work with large-scale structured and unstructured datasets using Python, SQL, and PySpark to build scalable data and ML pipelines
• Build and optimise cloud-native AI solutions and workflows on AWS
• Apply statistical analysis, feature engineering, experimentation, and model evaluation techniques to improve model performance
• Collaborate with engineers, product owners, and domain experts to solve complex business problems and deliver impactful AI solutions
• Support model deployment, monitoring, and continuous improvement of production ML systems
• Contribute to best practices across responsible AI, model governance, and ML Ops.

Essential Skills:

• 5+ years of experience in Data Science, Machine Learning, or Applied AI
• Strong hands-on experience with Python, PySpark, SQL, and AWS
• Experience working with large-scale datasets and distributed data processing frameworks
• Experience building, evaluating and deploying machine learning models in production environments
• Strong analytical, problem-solving, and stakeholder communication skills
• Exposure to Financial Crime, Fraud, AML, Risk, or Banking domains is highly regarded.
• Experience in building and shipping Generative and Agentic AI based systems.

Education Qualifications:

Bachelors, Masters or PhD in Statistics, Mathematics, Data Science, Computer Science, or related disciplines