Data Scientist, Semiconductor Manufacturing Analytics

Overview In this role, you apply advanced analytics and machine learning to improve Thermal Compression Bonding (TCB) processes, packaging, and yield. You will partner with process, equipment, metrology, quality, and manufacturing teams to translate complex problems into scalable data solutions that enhance performance and decision-making. You’ll build predictive models, monitor processes, and deploy analytics in production to drive measurable improvements. This position offers hands-on work at the intersection of data science and semiconductor manufacturing with a clear impact on yield and efficiency. Compensation / Benefitscompetitive paystock bonuseshealth benefitsretirement plansvacationon-site collaboration ResponsibilitiesAnalyze manufacturing, process, equipment, metrology, and yield data to uncover trends, correlations, anomalies, and root causes of variationDevelop and validate analytics and ML models for process monitoring, excursion detection, yield prediction, defect pattern analysis, and tool/process drift monitoringCreate proofs-of-concept to demonstrate feasibility of predictive analytics for TCB and related applicationsCollaborate with process and equipment teams to translate manufacturing problems into scalable data solutionsSupport advanced process control initiatives and deploy solutions in production environmentsDevelop dashboards, reports, and automated analyses to aid decision-making and reduce response timesMaintain data quality, model validity, and manufacturing relevance Key requirementsBachelor's degree with 6+ years of experience, Master's with 4+ years, or PhD with 2+ years in data-related disciplines2+ years of manufacturing data analysis and applying data-driven methods to solve process or yield problemsProficiency in Python and JMP for data analysis, automation, and model developmentExperience with large manufacturing, equipment, metrology, or quality datasetsExperience applying AI/ML, statistical methods, or predictive modeling to extract actionable insights for business or engineering decisionsSQL or other database query tools for data extraction and analysisStrong analytical and critical-thinking abilitiesClear communication of assumptions, risks, and recommendationsOwnership mindset and ability to drive initiatives from concept to implementationData science and machine learning for manufacturingStatistical analysis and predictive modelingPython programming