Job description 

About the role - you will:

• Assure the Reliability, Availability, and Serviceability (RAS) exceeds customer requirements during development through the utilization of proactive Design for Reliability (DFR) tools and techniques
• Integrate with program teams to evaluate and assure parts and complex system designs through systematic evaluation of Reliability, Availability and Serviceability
• Identify and mitigate contributing factors to field reliability, identified through statistical analysis of field performance data
• Resolve customer (internal & external) queries relating to the products design quality, RAS and field reliability performance
   

About you:

• Experienced in RAS modeling (Reliability Block Diagram, Monte Carlo Simulation, Markov State Diagrams)/ predictions (Telcordia SR-322/MIL 217) and statistical analysis, resulting in driving change as a result of their own analysis. 
• Understanding the working of DFR Activities like Reliability prediction, Availability modeling, FMEA, FTA, RBD, SPC, etc. 
• Experience of Electrical Design Analysis: Electrical stress analysis, Worst Case Electrical Parts Tolerance Analysis (WCEPTA), Evaluation of Life limiting Components, thermal analysis
• A detailed understanding of reliability modeling and statistical analysis, specifically:
• Understanding of Reliability mathematics terms Industry standards, specifications and applications
• Sound understanding and application of statistical methodologies including Weibull analysis and probability functions to evaluate lifetime analysis
• Ability to communicate effectively at all levels within the organization, external customers and suppliers 
   

Your experience includes:

• A broad electronic/electromechanical engineering & statistical background managing supplier, RAS activities, including planning, review and issue resolution 
• Proficient in collating and statistically analyzing data from multiple data sources. 
• Experience in the following quality assurance activities is desirable:
  • Identifying quality and reliability trends throughout a product's lifecycle 
  • Facilitate FMEA within engineering teams 
  • Availability modeling of complex systems 
  • Risk evaluation and predictive techniques 
  • Quality Assurance / reliability test methodologies 
  • Benchmarking