2027 Spring Data Scientist Co-op - Gloucester, MA

Applied Materials•Gloucester, MA

10h•Onsite

About The Position

Applied Materials’ Gloucester Applications Lab, Metrology team is seeking a motivated Data Scientist Co-op to help modernize statistical process control (SPC) and tool-health monitoring. The role combines data analytics, visualization, process improvement, and hands-on collaboration in a semiconductor applications-lab environment. The co-op will organize and streamline existing SPC charts and protocols, develop dashboards for rapid review, and improve how process technicians receive SPC pass/fail status and exception notifications. The assignment begins in January 2027, is onsite in Gloucester, Massachusetts, and lasts 6–8 months.

Requirements

Currently pursuing a BS, MS, or Ph.D. in Mathematics, Statistics, or Data Science.
Must be available to work full-time for a 6–8 month internship/co-op assignment and remain in student status.
Demonstrated programming experience and strong knowledge of statistical process control (SPC) using statistical software such as JMP, Python, MATLAB, or similar computational tools.
Strong analytical, problem-solving, and critical-thinking skills, including the ability to independently lead technical investigations and drive business productivity with minimal supervision.
Ability to adapt rapidly to new equipment, processes, and technologies, work effectively in shared research facilities, and adhere to cleanroom protocols.
Clear and effective written, verbal, and presentation communication skills for collaboration across multidisciplinary teams.

Responsibilities

Review, organize, and standardize existing SPC charts, control plans, and monitor protocols across metrology systems and process tools.
Support the lab data-repository initiative by consolidating and migrating data from legacy metrology tools, including TW and Rs systems, to a centralized network location.
Assess current SPC performance and identify charts, limits, or workflows requiring investigation or improvement, including processes with weak capability indicators such as Cpk.
Develop a centralized dashboard and data-visualization solution for reviewing SPC trends, tool health, and exceptions.
Create clear pass/fail status indicators and an alerting workflow to notify process technicians when a tool passes or fails an SPC check.
Automate or simplify recurring data collection, chart generation, review, and reporting steps where practical.
Partner with engineers and process technicians to define user requirements, test solutions, document workflows, and support adoption.
Prepare concise technical documentation and present project progress, findings, and recommendations to the Applications Lab team.