Predictive Data Analytics Intern - Summer 2026 at Lam Research

Tualatin, Oregon, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Apr, 26

Salary

0.0

Posted On

09 Jan, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Signal Processing, Anomaly Detection, Predictive Maintenance, Feature Extraction, Python, R, Data Visualization, Engineering Principles, Flow Dynamics, Thermofluid Systems, Analytical Skills, Problem-Solving, IoT Sensor Networks, Time-Series Analysis, Cloud-Based Analytics

Industry

Semiconductor Manufacturing

Description

The group you’ll be a part of In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry. The impact you’ll make We are seeking a Predictive Data Analytics Intern to develop advanced models and algorithms for predictive maintenance and process optimization. This role combines expertise in data science, machine learning, and engineering principles to analyze sensor and flow data, detect anomalies, and forecast equipment performance in complex industrial systems. What you’ll do Design and implement predictive maintenance models using sensor and flow data. Apply signal processing techniques for data filtering, feature extraction, and noise reduction. Develop and validate machine learning algorithms for anomaly detection and failure prediction. Collaborate with engineering teams to integrate predictive analytics into process control systems. Perform data visualization and reporting using Python, R, and relevant analytics tools. Ensure model accuracy through continuous monitoring and iterative improvement. Work with cross-functional teams to translate insights into actionable maintenance strategies. Who we’re looking for Field of Study: Current Masters or PhD students studying Data Science, Applied Statistics, or Mechanical Engineering with strong machine learning experience. Technical Skills: Signal Processing (sensor data filtering, feature extraction) Machine Learning / AI (predictive models, anomaly detection) Domain Knowledge (flow dynamics, thermofluid systems) Programming (Python, R for modeling and visualization) Strong analytical and problem-solving skills. Experience with industrial data sets and predictive maintenance applications is a plus. Preferred qualifications Familiarity with IoT sensor networks, time-series analysis, and cloud-based analytics platforms. Knowledge of reliability engineering principles and failure mode analysis. Hands-on experience with data pipelines and model deployment in production environments. Available to intern for 4-6 months starting Summer 2026. 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. IND123 #LI-CW1 Our Perks and Benefits At Lam, our people make amazing things possible. That’s why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.

Responsibilities

The intern will design and implement predictive maintenance models and develop machine learning algorithms for anomaly detection. They will collaborate with engineering teams to integrate predictive analytics into process control systems.