Analyze equipment, maintenance, and operational data to identify reliability risks, failure trends, bad actors, and improvement opportunities.
Develop and maintain reliability dashboards, scorecards, and key performance indicators that support data‑driven decision-making.
Conduct statistical analyses, reliability studies, and failure trend evaluations to support reliability improvement initiatives.
Provide actionable insights to reliability, maintenance, engineering, and operations teams to improve asset performance.
Support the development and optimization of predictive maintenance programs for critical manufacturing assets.
Analyze condition monitoring data, asset criticality rankings, and maintenance strategies to improve equipment reliability and maintenance effectiveness.
Develop asset health monitoring methodologies, predictive models, and leading indicators of equipment failure.
Evaluate the effectiveness of predictive maintenance technologies and identify opportunities for continuous improvement.
Develop predictive analytics, automated alerts, equipment health scoring systems, and reliability monitoring tools.
Utilize manufacturing, maintenance, and historian data to identify patterns, risks, and performance improvement opportunities.
Support reliability improvement initiatives through root cause analysis, performance tracking, and benefit realization reporting.
Develop reporting and analytics that support reliability governance, prioritization, and investment decisions.
Promote best practices and standard methodologies across reliability programs and manufacturing sites.
Quantify operational and financial benefits resulting from reliability and maintenance improvements.
Requirements
Bachelor's degree in Engineering, Data Science, Statistics, Applied Mathematics, Computer Science, Industrial Engineering, or related technical discipline; advanced degree preferred.
Minimum 10 years of experience in reliability analytics, manufacturing analytics, data science, reliability engineering, maintenance engineering, or related industrial roles.
Demonstrated experience developing predictive models, advanced analytics, and digital solutions that improve asset reliability and operational performance.
Experience working with manufacturing, maintenance, operational, and historian data in complex industrial environments.