- Location
- Melbourne, Victoria
- Type
- Full-time
- Department
- Education
- Closing date
- Today
- Source
- ApplyToJob
Description
Ray White is a household name in Australia and New Zealand, a name synonymous with the property and real estate industry, home lands, mortgages, and insurance. Established in 1902, in the small Queensland country town of Crows Nest, Ray White has evolved into Australasia’s most successful real estate business, now approaching 1,000 individual offices in Australia, New Zealand, and South East Asia. Last year, Ray White sold over $53 billion worth of property.
The Data Scientist supports Ray White Group's Economics function through the analysis, modelling and development of large-scale property market datasets and analytical systems. The role is responsible for developing statistical methodologies, data models, automated data pipelines and analytical products that transform complex property data into reliable market intelligence. The Data Scientist works across the full analytical lifecycle, including data acquisition, transformation, modelling, validation, analysis, visualisation and communication of results.
Key Responsibilities
- Statistical Analysis & Modelling: Develop, test, and refine statistical models for price indices, sales trends, and market forecasting across AU & NZ property markets.
- Data Engineering & Automation: Build and maintain automated data pipelines, integrating internal systems and external APIs to deliver analysis-ready datasets.
- Market Research & Insights: Conduct quantitative research on emerging real estate trends, providing evidence-based analysis for national media commentary and executive leadership.
- Stakeholder Collaboration: Translate complex quantitative findings into clear visualisations and actionable insights for non-technical corporate teams, local offices, and journalists.
Technical Requirements
- Core Tech Stack: Strong proficiency in SQL, Python, relational databases, and API integrations.
- Analytics & Modelling: Solid foundation in statistical analysis, quantitative modelling, and time-series analysis.
- Data Engineering: Experience with automated data pipeline creation, ETL processing, data quality, and validation systems.
- Data Visualisation & Reporting: Skill in developing interactive dashboards, automated reporting tools, and visualising property-market datasets.
- Communication: Proven ability to document technical methodologies and articulate complex analytical findings to non-technical stakeholders.
- Qualifications & Experience: Degree qualification in economics (or a related quantitative field) and relevant industry experience in real estate or financial markets.
Working With Us
Develop your career and gain valuable experience within a multifaceted business experiencing consistent growth, and in this role you have the opportunity to help improve the efficiency of our team by identifying and implementing process improvements.
We are invested in setting up our people for long-term success, engaging various professional programs, events, and initiative across the year to bring people to their full potential. We are also dedicated to fostering a culture of wellbeing by creating an inclusive and supportive work environment for all.
Ready to join a high-performing team that values curiosity, collaboration, and creating a meaningful impact? We'd love to hear from you!
Click Apply Now!
Develop your career and gain valuable experience within a multifaceted business experiencing consistent growth, and in this role you have the opportunity to help improve the efficiency of our team by identifying and implementing process improvements.
We are invested in setting up our people for long-term success, engaging various professional programs, events, and initiative across the year to bring people to their full potential. We are also dedicated to fostering a culture of wellbeing by creating an inclusive and supportive work environment for all.
Ready to join a high-performing team that values curiosity, collaboration, and creating a meaningful impact? We'd love to hear from you!
Click Apply Now!
Skills
PythonSQLData EngineeringETL