Asset and Optimisation Analyst

About the role

A newly created Asset and Optimisation Analyst position supports the Asset & Optimisation team in Service Stream's Transport division. The role helps execute technology and data initiatives for the 'Future Fit 28' strategy. The team is nationally dispersed, and the role can be based in Melbourne or Fortitude Valley.

Key responsibilities

• Standardise technology, data and analytical practices, improve information quality and accessibility, and turn asset and operational data into actionable insights.
• Support the responsible exploration, development and adoption of artificial intelligence solutions that strengthen asset management, operations and investment decisions.
• Establish consistent data standards, governance and analytical practices, define data requirements, improve data quality and validation, align projects to common Transport standards and document processes, ownership, controls and information flows.
• Analyse performance, condition, risk and cost trends, build dashboards and decision-support tools, and support lifecycle planning, maintenance prioritisation, investment programs and benchmarking.
• Cleanse and validate datasets, resolve root-cause data issues with data owners, set quality and adoption measures, and support pilots and continuous improvement.
• Identify practical AI use cases, contribute to analytics and automation tools, promote responsible AI governance and drive innovation through knowledge sharing.

Required profile

• Experience in data analysis, business analysis, asset management, digital delivery or operational improvement.
• Strong interest in AI and questioning how things can be done better.
• Ideal candidate: experience turning asset or operational data into decision-ready insights, ideally in civil infrastructure, construction, utilities or a similar field-service environment.
• Tertiary qualification in Engineering, Asset Management, Data Analytics, Information Systems, Business or a related discipline, or equivalent experience.

Required skills

• Knowledge of data lifecycle, data quality, governance and visualisation.
• Working knowledge of AI concepts; experience with AI, machine learning, predictive analytics or intelligent automation is highly desirable.
• Enterprise asset management or work management system experience.
• Power BI, SQL, Python, QGIS, Power Platform or cloud data exposure.
• Understanding of ISO 55001, lifecycle planning and risk-based prioritisation.

What we offer

• Hybrid working, with flexibility requests genuinely considered.
• Career development, internal mobility and online learning.
• Discounts on hundreds of businesses, novated leasing and a share matching program.
• Paid leave including parental, cultural, community service, defence, study, corporate volunteering and purchased leave.

Applications are submitted through the online application form, which directs candidates to create a profile and apply via Workday.