Fellow Product Performance Lead

Product Performance & Risk Insight Leads the identification and interpretation of emerging product performance risks through deep expertise in the products, post-market quality systems, product investigation, and industry best practices Integrates data across multiple domains; complaints, clinical, manufacturing, to assess system-level performance and detect patterns that may not be visible through traditional monitoring Defines and evolves analytical frameworks, methodologies, and best practices for post-market surveillance and signal detection, moving beyond traditional monitoring approaches Leads complex, high-impact investigations requiring deep technical judgment and cross-domain data integration Provides independent, evidence-based evaluation of product performance trends and monitoring strategies Process & Capability Development Evaluates the effectiveness of current signal detection and monitoring processes and drives continuous improvement Establishes scalable, repeatable, and measurable frameworks for product performance monitoring Serves as the technical lead across Quality, Medical Safety, R&D and Manufacturing to align on product performance insights and emerging risks Drive data-informed decision-making in high-visibility and time-sensitive situations with cross functional partners to ensure appropriate understanding and evaluation to influence decisions across design, risk, and quality Minimum of a Bachelors degree in Engineering or related fields Minimum of 10 years of experience in implantable medical devices with an emphasis in cardiac pacing, defibrillation, or diagnostics therapies and technologies. Demonstrated expertise in analyzing complex, multi-source data to drive technical conclusions and translate into actionable recommendations Proven ability to influence cross-functional decisions in a matrixed organization Masters degree Electrical Engineering or Computer Science degree Cardiac Rhythm Management Pulse Generator/Implantable Cardioverter Defibrillator/Systems experience Deep understanding of medical device quality systems and post-market surveillance Experience with advanced analytics, data science, or AI/ML applications Familiarity with clinical data interpretation, design controls, and risk management frameworks