Equipment Intelligence Specialist 4

Develop and apply expertise in Lam Equipment Intelligence (EI) platforms, including EI-DA, EI-App, Jupyter Notebook, Python and JMP, to deliver data-driven insights that improve tool productivity, capacity utilization, and fab performance. Use Lam's analytics capabilities to evaluate installed-base performance, support customer commitments, and strengthen customer confidence through meaningful operational and business outcomes. Design, develop and maintain scalable, well-documented and version-controlled analytical solutions, including Python applications, notebooks, dashboards and automated reporting systems. Transform large and complex datasets into actionable intelligence that supports productivity improvement initiatives, capacity ramps, performance optimization and fab management objectives. Partner closely with Global Product Equipment Intelligence teams, Account Teams, Global Product Support, CSBG, site organizations and customers to deploy, validate and enhance analytical solutions. Collaborate across functions to identify performance gaps, investigate issues, develop improvement strategies and achieve aligned business and operational targets. Translate site and product-level learnings into standardized, reusable workflows that can be scaled across regions, product groups and customer environments. Drive continuous improvement by adapting analytics methodologies and support models to evolving customer priorities, fab requirements and performance expectations by providing structured insights, trend analyses and data-driven recommendations that enable stakeholders to make informed decisions and accelerate performance improvement initiatives. Support both local and global leadership teams in achieving customer commitments and organizational goals through disciplined execution, effective communication and measurable outcomes. Promote worldwide knowledge sharing by documenting best practices, new methodologies and lessons learned, ensuring successful approaches are replicated across teams Contribute to operational reviews and strategic discussions by delivering concise executive-level analyses that highlight opportunities to improve productivity, installed-base performance, operational effectiveness and overall customer value PhD in Electronics, Chemistry, Physics, Material Science, or related field; or Masters of Science with 3+ years of relevant work experience; or Bachelors of Science with 6+ years of work experience. Proficiency in Python development, Jupyter Notebook, and analytical tools such as JMP; experience building maintainable, documented code with version-control practices Strong analytical capability with experience in multi-dimensional data analysis, including segmentation, reconstruction, classification, or manipulation. Excellent communication and cross-functional collaboration skills are required. In-depth understanding of Statistical Process Control (SPC) and/or Design of Experiments (DOE). Effective organizational skills and ability to manage multiple tasks simultaneously, reacting to shifting priorities, and meeting business needs and deadlines. Excellent interpersonal skills with the ability to work effectively with diverse teams, customers, and partners. Practical understanding of semiconductor fab operations, equipment productivity, and customer ramp environments. Ability to convert complex datasets into clear insights, executive-ready summaries, dashboards, and actionable recommendations. Continuous-improvement mindset with the discipline to document, standardize, and scale effective methodologies.