{"id":2843034,"url":"https://alion.io/job/entegris-lead-scientist-modeling-simulation","title":"Lead Scientist, Modeling & Simulation","company":{"id":7992,"name":"Entegris","domain":"entegris.com","url":"https://alion.io/company/entegris","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":76,"open_postings":67,"ghost_share":0,"stale_share":0.97,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Science & Research","role_family":"Science & Research","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hsinchu, 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datasets\n\nCollecting, cleaning, and transforming large datasets\n\nBuilding statistical / ML models\n\nIdentifying patterns and trends for business or engineering decisions\n\nDelivering predictive models, process optimization, and decision support\n\nCommunicating insights to cross-functional stakeholders\n\nIn this role you will:\nWork with RD, process engineers, equipment engineers and IT in the following areas and translate RD/engineering problems into data science frameworks.\nSupport the integration of datasets from multiple engineering/RD domains for data science applications (statistics, AI/ML, time-series analysis…).\nDevelop models for yield, quality, and defect predictionto support root cause analysis and anomaly detection for improvement in process control and productivity.\nBuild predictive models and deploy ML pipelines in production environments to support the development of AI-enabled solutions.\nDevelop physics-informed ML models or design new modeling approaches integrating computational simulation data and experimental data to solve scientific /engineering problems.\nTraits we believe make a strong candidate:\nGood communicationskills in both Mandarin and English.\n\nAteam player able to work with different stakeholders in diversified task forces.\n\nExperiences in chemical manufacturing, semiconductor manufacturing or related fields.\n\nMaster’s degree or PhD in data science, computer science, industrial engineering, chemical engineering, chemistry, physics or related fields.\n\nProficiency in collecting, cleaning and transforming large datasets and building data models based on statistics, AI/ML etc.\n\nProficiency in tools such as Python, R, TensorFlow,PyTorch, SQL or Tableau.\n\nAbility to do research independently to identify optimal solutions / approaches for target scientific or engineering problems.\n\nYour success will be measured by:\nAble to collaborate with diversified team members or stakeholders and deliver quality results on time.\n\nAble to probe stakeholders’needs and translate their problems into data science frameworks.\n\nAccountable for delivering high quality data science solutions for target problems.\n\nDedicated to improving solution quality continually.\n\nDetermined to attack difficult challenges with perseverance and creativity.\n\nPassionate to explore and develop data science applications in different areas.\n\nCurious to dive deeper into data science domain and keep abreast of latest developments.\n\nMotivated to acquire new knowledge and skills and apply them in solution development.\n\nAbleto accept coaching and grow himself/herself continuallywith a growth mindset.","description_format":"text","description_chars":2834,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All 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