We are looking for an Asset Modeller to join our Transport division responsible for developing and maintaining comprehensive asset models for our national road maintenance business. You will emphasise on predictive scenario modelling statistical analysis and innovative use of data often incomplete or imperfect to deliver insightful asset management solutions.

You will be based at our modern Head Office which offers a vibrant environment featuring a balcony BBQ area collaborative and quiet spaces and plenty of natural light.

About the role

Your key responsibilities will include:

• Develop and refine sophisticated predictive asset models using advanced statistical methods (e.g. regression analysis machine learning Monte Carlo simulations).

• Evaluate asset deterioration patterns predicting future performance under various scenarios to inform strategic maintenance decisions.

• Collect validate and integrate asset data from diverse sometimes fragmented sources.

• Maintain a centralised asset database ensuring high standards of data governance and accessibility.

• Perform detailed lifecycle cost analyses using statistical forecasting and predictive methods to optimise maintenance planning and capital investment decisions

• Utilise advanced digital tools (e.g. Brightly Predictor GIS BIM Digital Twins) to enhance asset modelling and monitoring capabilities.

• Provide expert technical guidance and analytics-driven recommendations to project teams contractors and operational staff.

• Proactively identify and advocate opportunities for improving asset performance and reducing costs through predictive insights and innovative solutions.

About you

Our ideal candidate will have:

• Minimum 8 years of experience in asset modelling predictive analytics data science or a closely related field.

• Demonstrated expertise in handling and interpreting large complex datasets including incomplete or uncertain data.

• Expert proficiency in statistical modelling predictive analytics and scenario-based forecasting. Hands-on experience with data analytics tools such as Python R or SQL.

• Tertiary qualification in Engineering Data Science Statistics or related quantitative disciplines.

• Membership or eligibility for membership with the Institution of Engineers Australia.

• Professional Engineer (PE) registration or eligibility for registration in Australia is preferred.

• Deep familiarity with asset management software (GIS BIM digital twins Brightly Predictor) and advanced predictive maintenance tools.

• Strong capability in managing cleansing and enhancing large-scale asset datasets including managing data gaps and inaccuracies

• In-depth understanding of road and roadside infrastructure assets and their deterioration patterns.

About us

Service Stream is an equal opportunity ASX-listed business that develops and operates Australias essential services networks across telecommunications utilities transport defence and social infrastructure industries.We keep communities connected.

Benefits of working with us include

• Flexible working- All flexibility requests are genuinely considered. This position offers hybrid working.

• Growth We are growing and there are opportunities for your career development across our business units.

• Discounts- Access to hundreds of businesses such as Woolworths Air BNB The Iconic JB HI-FI Dan Murphys Bupa Health Care and Specsavers. We also offer access to novated leasing.

• Paid leave- Parental cultural community service study corporate volunteering and purchased leave available.

• Culture We are dedicated to fostering a workplace environment that values diversity and inclusion and we recognise and celebrate excellence throughout the year.

How to apply

Please submit your interest with the apply button where you will be directed to create a profile on our system. We celebrate diversity at Service Stream and would welcome applications from people who identify as Aboriginal and/or Torres Strait Islander people with a disability or neurodivergence and those from LGBTIQA Veteran or other diverse groups.

Applications will not be accepted via email. If you require any reasonable adjustments to the recruitment process please email .