Predictive Data Analytics Intern - Summer 2026 - Winter 2026Lam Research • United States
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Predictive Data Analytics Intern - Summer 2026 - Winter 2026
Lam Research
- United States
- United States
Über
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.
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.
Sprachkenntnisse
- English
Hinweis für Nutzer
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