Mgr, Global Operations Analytics & AI Enablement

Lam Research•Tualatin, OR

37d

About The Position

As an Operations Analyst Manager at Lam Research, you will lead a team of 8–10 Operations Analysts responsible for actionable insights, scalable reporting, operational analytics, and process improvement across Global Operations. You will provide leadership, coaching, prioritization, and accountability so the team delivers high-quality data products, analytical standards, and business recommendations that improve operational performance. You will also help integrate artificial intelligence into scalable solutions and governed datasets to enable predictive analytics, automation, and faster decision-making across the organization. The Global Operations Group brings together information systems, facilities, supply chain, logistics, and high-volume manufacturing to support Lam’s global business operations and resilient, profitable growth.

Requirements

Bachelor’s degree in business, supply chain, engineering, data analytics, operations, or a related field, with 4–6 years of supervisory experience; or equivalent experience.
Demonstrated experience leading, supervising, or mentoring professional analysts or analytical teams in a global, matrixed operations environment.
Strong experience developing data visualizations, reports, dashboards, and business insights using Power BI, Excel, SAP Business Objects, or similar platforms.
Demonstrated ability to define analytical standards, govern datasets, improve data quality, and ensure reporting accuracy across stakeholders and business processes.
Experience applying AI, automation, predictive analytics, or advanced analytics concepts to improve operational efficiency, decision-making, and scalability.
Proficiency in process improvement methodologies, change management, and operational excellence practices.
Strong knowledge of planning, order execution, supply chain, manufacturing, logistics, or related semiconductor operations processes.
Ability to influence cross-functional stakeholders, challenge assumptions, and align teams toward long-term, data-driven solutions.
Excellent communication, executive presentation, coaching, and stakeholder management skills.

Nice To Haves

Advanced degree preferred.
MBA or equivalent advanced degree.
Experience leading analytics or digital transformation teams supporting Global Operations, Order Management, Order Execution, Manufacturing, Supply Chain, Production Planning, or related functions.
Hands-on experience with AI-enabled analytics, machine learning concepts, data pipelines, semantic models, or governed enterprise datasets.
Lean Six Sigma Black Belt or equivalent continuous improvement certification.
PMP or equivalent project/program management certification.
Semiconductor industry experience highly preferred.

Responsibilities

Lead, coach, and develop an Operations Analyst team supporting Global Operations analytics, reporting, dashboards, and process improvement initiatives.
Set team priorities, operating cadence, performance expectations, and accountability mechanisms to ensure timely delivery of high-impact analytical solutions.
Drive the development, automation, and governance of scalable reporting solutions, dashboards, datasets, and self-service analytics.
Integrate AI-enabled capabilities into operational workflows, datasets, and analytics solutions to reduce manual effort, improve decision quality, and enable predictive insights.
Partner with business, digital transformation, and functional stakeholders to identify high-value automation and AI use cases aligned with operational priorities and measurable business outcomes.
Ensure compliance with analytical standards, data governance policies, access controls, and data integrity requirements across team-owned datasets and reporting solutions.
Translate complex operational data into clear insights, executive-ready narratives, and actionable recommendations for leadership decision-making.
Identify process gaps, operational risks, and performance trends; lead development of data-driven recommendations and scalable countermeasures.
Facilitate change management for new data products, AI-enabled tools, and process changes to support adoption, sustainment, and measurable value realization.
Measure and publish operational performance against established metrics and targets, while continuously improving reporting accuracy, usability, and business relevance.