Principal Data Scientist

• It s fun to work in a company where people truly BELIEVE in what they re doing!
• We re committed to bringing passion and customer focus to the business.
• If you like wild growth and working with happy, enthusiastic over-achievers, you ll enjoy your career with us!
• Lead the data-science and advanced-analytics agenda for FAB and factory operations.
• Partner with manufacturing and engineering leaders to frame problems, define analytical requirements, and prioritize analytical work.
• Analyze FAB and factory processes, including yield, process variability, excursions, equipment behavior, throughput, bottlenecks, cycle time, WIP, rework, test fallout, quality, and scrap.
• Develop and apply statistical, predictive, and prescriptive models using complex, high-volume manufacturing data.
• Design and evaluate experiments, including DOE and controlled analyses, to understand process drivers and validate improvement actions.
• Apply regression, multivariate analysis, time-series methods, anomaly detection, causal reasoning, SPC, and other advanced statistical techniques.
• Establish trusted analytical definitions, features, and data structures across lots, products, process steps, equipment, recipes, materials, test results, defects, and production events.
• Work with data engineering and platform teams to productionize datasets, features, models, and analytical applications.
• Support analytics across MES, SPC, FDC, R2R, equipment, test, quality, ERP, supply-chain, and planning systems.
• Review analytical methods and results for statistical rigor, data quality, interpretability, and practical usability.
• Communicate technical findings, assumptions, uncertainty, tradeoffs, and recommendations to engineers, operators, business leaders, and executives.
• Build reusable analytical methods, documentation, validation standards, and model-monitoring practices.
• Mentor data scientists, analysts, and engineers in statistical thinking, problem framing, modeling, and technical communication.
• Represent Corporate Analytics & Data Science as a trusted technical advisor to manufacturing and operations leadership.
• Job Qualifications:**
• Ph.D. or Master s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 15 years of progressive experience in data science, applied statistics, manufacturing analytics, process engineering, yield engineering, operations research, or a closely related discipline.
• Advanced degree in statistics, data science, industrial engineering, electrical engineering, materials science, physics, operations research, or a related quantitative field; equivalent experience may be considered.
• Demonstrated experience applying advanced analytics and statistical modeling in photonics, semiconductor, optical-component, wafer, electronics, or similarly complex manufacturing environments.
• Deep understanding of FAB and factory processes, including process control, yield analysis, equipment behavior, production flow, test, quality, and manufacturing execution systems.
• Expert knowledge of experimental design, DOE, regression, multivariate analysis, time-series modeling, anomaly detection, causal analysis, and statistical process control.

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