Join Suncorp’s AI & Data Science Centre of Excellence, where we harness the power of data to drive real business performance. Our mission is to maximise the value of data through innovative use cases, scalable AI solutions, and strategic support across the Group. We accelerate the value of Suncorp’s data investments by:

• Delivering high-impact use cases through experimentation, prototyping, and production-grade AI and Data Science solutions embedded at scale across the business
• Empowering strategic leaders and the broader data science community with expert guidance, best practices, and governance to ensure the right initiatives are delivered effectively
• Be part of a team that shapes Suncorp’s AI & DS ecosystem - including platforms, tools, and governance frameworks-to enable smarter decisions, faster innovation, an

This is a 2 year contract role.

What you’ll do

• Partner with stakeholders to solve complex business problems using innovative, value-driven data science solutions
• Design, develop, and deliver advanced data science components (e.g. models, algorithms) within an agile framework
• Ensure quality, governance, and risk management of all data science outputs
• Provide deep technical expertise and guidance in data science and machine learning
• Lead and collaborate effectively within teams, offering technical or people leadership as needed

What you’ll bring

• Strong results in a relevant technical bachelor's degree e.g. statistics, actuarial, engineering, maths (mandatory)
• Postgraduate qualification or honours (Class 1 or 2A) in data science/statistics (desired)
• Understanding of Generative AI, including prompt engineering, RAG, and agents
• Highly valued: Experience deploying GenAI solutions in production
• Minimum 5 years in complex commercial data science or multivariate analysis
• Advanced expertise in one or more data science/analytics areas with proven delivery of complex models
• Proficient in machine learning and multivariate predictive analytics (e.g. GLMs, NLP, GBMs)
• Strong commitment to continuous technical learning and adaptation