Equipment Intelligence Specialist 4

Lam Research•Apply•Published 1 days ago•First seen 54 minutes ago

The group you’ll be a part of

The Customer Support Business Group focuses on enabling our customers with premier customer support throughout their lifecycle with Lam. We drive performance, productivity, safety, and quality of customers installed base performance and deliver service and lifecycle solutions for their most critical equipment and processes.

The impact you’ll make

The Equipment Intelligence Specialist will support Productivity and Fab Management programs by applying Lam Equipment Intelligence software applications and developing new analytics methodologies, dashboards, and notebooks to address business needs. This role serves as a Productivity Data Science Specialist for Lam Deposition, Etch, Wet, and Clean product lines within strategic customer accounts, with a focus on enabling customer capacity ramp, productivity improvement, installed-base performance, and Lam business performance.

What you’ll do

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

Who we’re looking for

Minimum Qualifications:

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.

Preferred qualifications

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.

Our commitment

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.