Develop and deploy data science, AI, and machine learning solutions, including LLM, RAG, and agentic workflow applications. Evaluate model performance, scalability, and stability; transition prototypes into production with Product, Engineering, and Data Engineering teams. Apply privacy, security, and responsible AI practices, monitor industry trends, and communicate technical recommendations to varied stakeholders.
About the role:
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
Key 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:
- 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.
Desirable experience
- 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.
Ray White Melbourne, Victoria, AUS Office
35 Collins Street, Melbourne, Australia
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