Data Scientist

Job Responsibilities

Lam Research is looking for a Performance Data Scientist in Lam’s Global Quality organization.  This is individual will partner with the Field/Factory Business Process Quality Manager, Global Quality peers and leaders across the company to identify through the use a common data to effectively prioritize and resolve the largest quality issues in the company impacting our customers and limiting our ability to meet both short and term business objectives.  This role will have a high-profile presence within the organization and will be able to contribute and make a difference in the quality performance and culture through knowledge, leadership and influence within the company and ultimately delivering required improvement to our valued customers and internal functions.

Essential functions/duties:

• Improve quality performance consistently from awareness, prioritization and action through the availability of common data.

• Analyze trends and patterns in quality data that drive required quality improvement.

• Develop tools, metric measurement and assessment methods for performance management and predictive modeling.

• Foster growth and utility of Cost of Quality within the company through correlation of I&W data, ECOGS, identification of causal relationships for quality events and discovery of hidden costs throughout the network.

• Reliability tracking and improvement and problem resolution.

• Improve data utilization via AI, automation and improve defect determination leading to real time resolution and speeding systemic action.

• Create accountability for corporate-wide quality data analysis and action.

• Lead and/or advise on multiple projects simultaneously and demonstrate organizational, prioritization, and time management proficiencies.

Minimum Qualifications

• Minimum 5 to 7 years of proven continuous improvement analytical experience from a similar role, including project management and business analysis.

• BS degree in engineering, quality management, computer science, related/applicable science, or master’s degree.

• Semiconductor industry experience.

• Proficiency in advanced statistics, knowledge of statistical methods for modeling multivariate data sets including machine learning techniques and other methods for modeling physical or electro-mechanical systems.

• Exceptional knowledge and history of implementation of AI to solve the most complex challenges of the Lam that lead to efficiency and effectiveness improvements.

• Ability to define problem statements and objectives, development of analysis solution approach, execution of analysis or experiments.

• Proven ability in leading, running, overseeing and directing large/complex programs and projects for internal and external end-users from discovery through maintenance and support.

• Must be able to influence in a fast-paced, cross-functional, matrixed organization.

• Solid communication, collaboration, interpersonal and influencing skills.

• Knowledge of programming environments such as Python, R, Matlab, or equivalent.

• Knowledge of Lean Six Sigma processes, statistics or quality systems experience.

• Ability to work on multiple problems simultaneously.

• Knowledge of Quick base, Power BI capability and development.

• Ability to present conclusions and recommendations to executive audiences.

• Excellent people skills and ability to work in matrix environment.

Preferred Qualifications

• Demonstrated success in using structured problem-solving methodologies and quality tools to solve complex problems.

• Command over quality tools such as Pareto FMEA /Fault tree diagram/Fish bone diagram etc.

• Willingness adapt best practices via benchmarking.

• Knowledge of programming environments such as Python, R, Matlab, or equivalent.

• Six Sigma certification (Green Belt or higher).

• Advanced expertise in structured problem-solving methodologies (PDCA, DMAIC, 8D) and quality tools.

• Experience in semiconductor capital equipment industry.

• Experience in Statistical Process Control (SPC), Gage R&R, Pareto Charts etc. using tools like JMP, Minitab.

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.

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