Data Scientist – Predictive Maintenance

About the role

The Data Scientist will help the Maintenance team better utilise existing data sources and train deployable predictive maintenance models to improve the reliability and lifecycle performance of PhotonAssay™ automation, detector and linear accelerator systems.

Key responsibilities

• Analyse maintenance and fault data to identify recurring failures and reliability risks.
• Perform data analytics and visualisations to provide actionable insights.
• Develop and refine condition monitoring and preventive maintenance strategies for PhotonAssay automation, detector and accelerator systems.
• Train reliable and deployable Machine Learning models for predictive maintenance.
• Optimise maintenance tasks and frequencies using data rather than fixed schedules, and incorporate approved strategies into MaintainX configuration, workflows, and maintenance programs.
• Support accurate capture of fault, maintenance, and spares consumption data, improving data quality and reporting discipline.
• Analyse data to prepare structured insights and business impact assessments for prioritising improvement initiatives.
• Use automation, detector and linac records for trend analysis and develop dashboards.
• Support spare parts optimisation by linking failure rates to criticality, stocking levels, and lifecycle forecasts.

Required profile

• Strong analytical mindset with ability to work with large maintenance and fault datasets.
• Experience in developing and deploying predictive maintenance models.
• Ability to translate data insights into actionable maintenance strategies.
• Familiarity with maintenance management systems such as MaintainX.
• Collaborative approach to work with maintenance leaders and site teams.

Required skills

• Machine Learning
• Data Analytics
• Data Visualization
• MaintainX (maintenance management system)