Data Science and Analytics - PhD Intern

Intel•Hillsboro, OR

1d•Onsite

About The Position

Join Intel as a Data Science and Analytics Graduate Intern, where you'll dive into analyzing large datasets to uncover meaningful insights that drive business decisions and enhance user experiences across Intel's platforms. In this role, you will contribute to building data models, dashboards, and visualizations while collaborating with cross-functional teams to deliver impactful, data-driven solutions. Through hands-on projects, you'll gain valuable knowledge and practical skills that will prepare you for future career opportunities in data science and analytics. Business group Intel Foundry is at the forefront of innovation, delivering cutting-edge solutions that enable Intel's success in the competitive semiconductor industry. Within Intel Foundry, the LTD Device PDK and Product team works to optimize products and processes by leveraging advanced technology, analytics, and data-driven approaches. This organization plays a key role in supporting Intel's broader mission to shape the future of computing and engineering through collaboration, innovation, and teamwork.

Requirements

Pursuing a PhD degree in a relevant field, such as data science, computer science, statistics, Electrical Engineering, Physics, Material Science, Computer Science or scientific field of study directly related to Semiconductor with 0-1 years of hands-on experience in data analytics or programming, demonstrated through internships, academic projects, coursework, or hands-on training.
Minimum of 6 months of experience in one or more of the following: Semiconductor materials, fabrication, and device physics
Electrical characterization of Semiconductor Devices (transistor, diode, etc.)
Familiarity with statistical methods and techniques used for data analysis.

Nice To Haves

Advanced Transistor Device Structures and Device Physics.
Process monitoring
Test structures design and layout experience.
Device and circuit simulation.
Statistical Process Control (SPC) or Design of Experiments (DOE) principles and engineering analysis tools experience.
Expertise in database structures, research methods, analytics packages (i.e., JMP, MATLAB, Octave), scripting languages (i.e., JSL, Perl, TCL), or programming languages (i.e., Python, SQL, C/C++).
Expertise in agentic AI and orchestrated LLM workflows, machine learning, deep learning, Retrieval-Augmented Generation (RAG), knowledge engineering, and dataflow pipeline architectures.
Strong communication and collaboration skills to work effectively in a team environment.

Responsibilities

Collect, analyze, and interpret large datasets to uncover patterns, trends, and actionable insights.
Assist in building predictive models, dashboards, and visualizations that support business objectives and improve user experience.
Collaborate with data scientists, analysts, and engineers to contribute to data-driven projects and solutions.
Apply statistical techniques and programming skills to support storytelling and decision-making processes.
Participate in hands-on learning opportunities, gaining real-world experience relevant to Intel's business goals.