Role Purpose
This role is responsible for performing complex engineering modelling and predictive analysis of tramway systems and components using specialist tools such as Assetic Predictor, Arcadis EDA, and other relevant modelling frameworks. The position delivers high-quality analytical outputs and modelling reports to inform and support engineering and asset management stakeholders.
A key function of the role is to support investment modelling, dashboard development (e.g., Power BI), and advanced data analytics that contribute to strategic business planning and decision-making. These activities directly support asset renewal planning, maintenance optimisation, and improvements in operational practices, ensuring alignment with broader business objectives.
The role achieves its purpose by developing and implementing forecasting models, automation tools, and reporting mechanisms for key systems and processes. It also provides comprehensive data analytics services and actively engages with internal and external stakeholders to deliver insights and drive alignment with the organisation’s asset management and strategic goals.
Responsibilities
- Apply advanced engineering modelling techniques to support informed asset decision-making.
- Develop, calibrate, and maintain predictive models for various asset types and systems.
- Conduct in-depth data analysis to identify trends, risks, and areas for optimisation.
- Research and integrate new modelling methods and technologies to drive innovation.
- Translate complex analytical findings into clear, actionable insights for stakeholders.
- Work closely with engineering, operations, and business teams to understand needs and deliver tailored solutions.
- Support continuous improvement by embedding data-driven approaches in asset planning and management.
Skills
- Advanced proficiency in modelling, simulation, and statistical analysis.
- Competence in Python, R, SQL, and relevant modelling platforms (e.g., Assetic Predictor, Arcadis EDA, or custom-built simulators).
- Experience with geospatial analysis tools (e.g., QGIS).
- Strong data visualisation capabilities using tools such as Power BI and Tableau.
- Excellent communication skills, with the ability to translate technical concepts for diverse audiences.
Knowledge and Experience
- Proven experience in developing and/or maintaining modelling frameworks or simulation tools.
- Strong foundation in data science methodologies (e.g., regression, classification, time-series analysis).
- Demonstrated ability to analyse large datasets to uncover trends and generate actionable insights.
- Experience collaborating across technical and non-technical teams.
- Tertiary qualifications in Engineering, Mathematics, Data Science, Computer Science, or a related discipline.