Commonwealth Bank is an Australian financial services company spanning retail, premium, business, and institutional banking. Its offering also includes funds management, superannuation, insurance, investment, and sharebroking services. With more than 52,000 employees and over 800,000 shareholders, Commonwealth Bank operates across a broad range of financial products and services designed to help customers manage and build their finances.
Senior Data Science Chapter Lead – Fraud, Scams & Cyber (Hybrid, Sydney)
Lead data science teams developing machine learning, generative AI and agentic AI solutions for Commonwealth Bank’s fraud and scams protection. Guide responsible AI delivery from experimentation through production deployment and monitoring.
Description
- Lead machine learning, generative AI and agentic AI initiatives supporting strategic business and customer outcomes
- Use statistical analysis and structured problem-solving to address complex fraud and scams challenges
- Take solutions from discovery and experimentation through validation, deployment and continuous monitoring
- Build generative AI capabilities using retrieval-augmented generation, orchestration, guardrails and agentic systems
- Expand the effective and responsible application of data science, machine learning and AI across fraud and scams
- Collaborate with product, engineering, platform, architecture, MLOps, risk and business teams
- Frame problems, assess trade-offs and turn technical findings into practical decisions
- Set technical standards for data and feature engineering, model selection, evaluation, testing, documentation and production release
- Develop the data science chapter through coaching, knowledge sharing, technical direction and collaboration
Requirements
- Demonstrated experience leading teams or providing substantial technical direction for machine learning, generative AI or agentic AI programs
- Strong grounding in statistics, probability and machine learning
- Hands-on experience building and assessing production AI or machine learning systems, including large language models, natural language processing or conversational AI
- Advanced proficiency in Python
- Experience with SQL and appropriate machine learning or deep learning frameworks
- Experience connecting AI systems to data pipelines, services and enterprise platforms
- Background working with MLOps teams and production delivery processes
- Practical experience with AWS or Azure, version control, continuous integration and delivery, containerization, monitoring and observability
- Knowledge of responsible AI, model governance, risk controls and documentation in a regulated or similarly complex setting
- Clear written and verbal communication skills
- A tertiary qualification in data science, statistics, computer science, engineering, mathematics or a related field is beneficial
Benefits
- Flexible working arrangements combining office time with remote work
- An inclusive, respectful environment supporting diverse cultures, abilities, genders, gender expressions and sexual orientations
- Support for Australia’s First Nations peoples
- Accessibility assistance available through HR Direct