Director, System Performance & Reliability Analytics

Description

• Lead and participate in the engagement with C3 AI during the 2 year Reliability partnership.
• Develop and implement advanced alerting systems and visual dashboards to monitor regional, product-specific, and operational deviations.
• Lead enterprise-wide problem-solving efforts, facilitating collaboration across Service, Operations, Engineering, and Quality teams.
• Lead the strategic direction and execution of fleet performance analytics, utilizing the reliability performance models, and field data to drive predictive insights and early anomaly detection.
• Oversee data validation and analysis using Python, SQL, and statistical tools to ensure high-quality insights and support executive decision-making.
• Collaborate with Engineering, Quality, Field Service, and AI teams to accelerate root cause investigations and corrective actions.
• Deliver high-impact presentations to internal and external stakeholders, translating complex technical analyses into strategic recommendations.
• Champion automation of analytical workflows to enable scalable and efficient fleet monitoring.
• Define and communicate a clear vision for data-driven reliability engineering, aligning cross-functional teams and fostering a culture of innovation and continuous improvement.
• Facilitate the execution of automated inspection through pattern detection from learning models to improve efficiency on the production floor and reduce quality escapes in station.
• Monitor and report on cost-of-poor-quality metrics, driving initiatives to reduce inefficiencies and improve product lifecycle economics.
• Define and execute strategies for utilizing fleet data that reduces overall service cost by enabling predictive product failure using deep learning algorithms to identify anomalous behavior that is correlated to the physics of the product failure modes and degradation.
• Integrate data from diverse sources to identify systemic degradation patterns and inform strategic reliability initiatives.

Requirements

• Bachelor’s or Master’s degree in Data Science, Mechanical, Electrical, Chemical, Reliability, or Systems Engineering; advanced degree preferred.
• Data-Driven Decision Making
• Strong business acumen with the ability to translate technical insights into strategic initiatives.
• Strategic Thinking & Vision Setting
• Expertise in data mining and analytics using Python, SQL, and statistical tools (JMP, Minitab); Tableau experience preferred.
• Strong understanding of reliability engineering methodologies including Fault Tree Analysis, Reliability Block Diagrams, and Markov modeling; experience with Reliasoft or equivalent tools is a plus.
• Visionary mindset with a passion for leveraging data to drive innovation, operational excellence, and long-term product reliability.
• Exceptional communication and presentation skills, with the ability to influence senior leadership and guide cross-functional alignment.
• Skilled in RCCA methodologies (Six Sigma, 8D) with experience solving complex problems and driving corrective actions.
• Proven track record of building and leading high-performing teams across technical and business functions.
• 12+ years of experience in product reliability, performance analytics, or systems engineering.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance