KLA Product Engineer – Reliability Modeling & Statistics 

United States, Michigan, Ann Arbor 

633566315

Job Scope and Complexity:

• Initially understand reliability models, then gradually own and run them to generate engineering insights

• Identify gaps between models and real-world scenarios, and develop innovative ideas to bridge these gaps with clever assumptions

• Write code as necessary to develop a fundamental understanding of reliability and statistical problems, and present insights and visualizations concisely

• Collaborate with cross-functional groups to obtain extensive data from the field and validate model results against field results

• Continuously drive innovation and features in the reliability, availability, and maintainability modeling domain

• Deliver written periodic reports to keep the wider team informed about status and progress

• Present ideas and results in concise decks and summary documents

• Lead cross-functional technical groups, convey key ideas, resolve differing viewpoints with a collaborative spirit, and move discussions forward

• Eager to learn and adept at picking up new technical concepts and software

• Be self-driven with a drive for problem-solving

Preferred Qualifications:

• Familiarity with any commercial reliability software (e.g., ReliaSoft)

• Demonstrated experience with part level and system level reliability analysis. Experience with reliability analysis of complex equipment systems a plus.

• Experience with failure mode analysis

• Familiarity with SQL and PBI

• Demonstrated experience using statistical and visualization packages for problem solving (e.g., JMP, Matlab, R, Python, PBI, Tableau, etc.). Familiarity with SQL is a plus.

• Master’s degree or doctorate in related discipline is preferred

• Experience in the framework of a Product Life Cycle and SEMI E10 definitions is a plus

Minimum Qualifications

• Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

• Degree in mechanical engineering, electrical engineering, computer science engineering, statistics, or related engineering discipline

• Demonstrated experience of advancing solutions to technical problems in a cross-functional and multidisciplinary environment

• Evidence of learning new software and adaptability to continuously learn new technical topics

• Evidence of applying statistics in solving real world industrial problems. A strong understanding of statistical distributions and their applications in real world (e.g., Weibull, exponential, etc.)

• A strong grasp of basic probability concepts. An understanding of Bayes’ probability framework is considered a plus.

• Evidence of proficiency in coding to solve applied industrial problems

• Strong interpersonal and communication skills