Technical Specialist - Reliability Core

Job Summary

As Technical Specialist - Reliability Core, you will provide expert technical leadership in reliability engineering, maintenance strategy development, and asset performance improvement. You will lead complex Reliability Centered Maintenance (RCM) studies and reliability improvement initiatives across operating assets, turning equipment history, risk information, and operational insight into practical maintenance and improvement strategies. This is a hands-on specialist role with a strong consulting and facilitation element. You will work with multidisciplinary asset teams, challenge technical assumptions constructively, assure the quality of reliability studies, and coach others in the effective application of reliability methods. You will also help teams make better use of analytics, digital tools, and emerging AI capabilities where these can deliver clear business value.

What you'll be doing

Reliability Strategy & Asset Care

• Apply reliability methods such as RCM, FMEA, RAM analysis, Weibull analysis, Fault Tree Analysis, and lifecycle cost analysis to support sound technical decisions.

Reliability Engineering & Continuous Improvement

• Identify recurring equipment failures, bad actors, and performance gaps, and lead structured reliability improvement activities to address them.
• Lead or support Root Cause Failure Analysis and Causal Learning investigations for significant or repeat equipment failures.
• Develop recommendations that are technically robust, proportionate to risk, and practical for asset teams to implement.
• Capture lessons learned and use them to improve reliability work processes, tools, and ways of working.

Reliability Statistical Analysis

• Apply advanced reliability statistical techniques to evaluate failure behaviour, predict equipment performance, and support maintenance strategy optimization.
• Perform Weibull Analysis, Crow-AMSAA Reliability Growth Modelling, and other probabilistic methods to assess failure patterns, reliability trends, and system improvement opportunities.
• Develop and utilize Monte Carlo Simulations to quantify uncertainty, assess risk scenarios, and support asset investment and lifecycle decisions.
• Conduct Remaining Useful Life (RUL) assessments and degradation modelling to support predictive maintenance, asset health monitoring, and intervention planning.
• Lead Asset Life Extension (ALE) studies by evaluating equipment condition, failure risk, operating context, and life-cycle economics to support safe and reliable operation beyond original design life.
• Translate statistical findings into actionable recommendations that improve asset availability, reliability performance, maintenance effectiveness, and business value.

Reliability analytics, digital and AI solutions

• Analyse equipment and maintenance data to identify failure trends, reliability risks, bad actors, and optimization opportunities.
• Develop or support reliability KPIs, dashboards, and analytical insights that enable timely and informed decision-making.
• Use reliability statistics and modelling to support maintenance, risk, and investment decisions.
• Identify practical opportunities for predictive maintenance, asset health monitoring, and AI-enabled reliability solutions.
• Collaborate with digital, analytics, and data science teams to translate reliability challenges into usable, value-focused solutions.
• Support adoption of digital reliability tools, intelligent agents, and data-driven workflows, with appropriate attention to data quality and user needs.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.