Data Scientist

• As a Data Scientist in the Data & Analytics team, you will be responsible for developing data driven, AI and ML solutions to deliver value to the organisation.
• You will work with business stakeholders, data engineers, data modellers, software engineers and analysts in cross functional teams to deliver end-to-end outcomes.
• You will also get opportunities to build proof of concepts to determine the value of
• AI/ML solutions to push the boundaries to create value for our brokers and their
• Clients.
• This is a hybrid role (2 days in the office per week) that can be done from Sydney, Melbourne or Brisbane

Responsibilities

• Design, develop, and implement machine learning solutions tailored to solve problems in a practical and timely manner.
• Develop and improve AI solutions using large language models (LLMs), retrieval-augmented generation (RAG), and agentic workflows that use tools and business systems to complete tasks.
• Evaluate the performance, stability, and scalability of developed models, ensuring they meet the necessary business requirements and standards.
• Work with Product, Engineering and Data Engineering to take solutions from experimentation into production and integrate them into existing products and workflows.
• Apply appropriate privacy, security and responsible AI practices when working with business data and AI systems.
• Stay abreast of industry trends, advancements, and innovations in AI, machine learning, and data science, driving continuous improvement and innovation within the team.
• Communicate technical insights and recommendations clearly and effectively to both technical and non-technical stakeholders.
• To succeed in this role you will bring with you:

Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, or a related quantitative field.
• 2+ years of hands-on experience in data science, including model development and deployment.
• Proficiency in Python and SQL for data manipulation and machine learning model development.
• Practical experience building applications with LLMs, including prompt development, retrieval or tool use.
• Problem-solving skills and the ability to translate business problems into data science solutions.
• Good communication skills with the ability to present findings and technical solutions to diverse audiences.

Preferred

• Deploying or supporting AI solutions in production.
• Working with cloud services, modern data platforms, APIs and automated deployment pipelines.
• Experience with dbt or similar data transformation tools.