Manager, Predictive Maintenance & Data Science

Role overview

Strategy and reliability

• Define the predictive maintenance strategy and capability roadmap around business objectives and customer needs.
• Improve condition-based and predictive maintenance capabilities across the global fleet.
• Use aircraft operational, maintenance, and health-monitoring data to improve fleet performance and maintenance outcomes.
• Lead reliability initiatives and oversee fleet health monitoring, investigations, root cause analyses, and reliability indicators.

Analytics and team leadership

• Lead data science, machine learning, engineering analytics, and predictive maintenance teams and solutions.
• Ensure models are actionable, explainable, scalable, and aligned with customer and business objectives.
• Develop team objectives and capabilities; support performance, recruitment, employee development, and career growth.

Delivery and collaboration

• Work with data platform and software teams to operationalize analytics and create customer-facing digital capabilities.
• Coordinate with engineering, technical services, customer response, field service, aircraft specialists, suppliers, and research partners.
• Track delivery, fleet reliability, maintenance effectiveness, customer adoption, and business value; manage budgets, resources, partnerships, and vendors.

Candidate qualifications

• University degree in Aerospace Engineering, Mechanical Engineering, Systems Engineering, Reliability Engineering, Computer Science, Data Science, or a related field.
• At least 10 years of experience in aerospace engineering, reliability engineering, predictive maintenance, data science, or related domains.
• At least 5 years of experience leading technical or multidisciplinary teams.
• Experience with aircraft systems, maintenance operations, reliability programs, fleet performance, or aircraft health-monitoring solutions.
• Strong business and strategic mindset, with the ability to translate technical capabilities into outcomes.