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Computer Science / Data Science Intern
Computer Science / Data Science InternGrowTech Industries, LLC • Goodyear, AZ, US
Computer Science / Data Science Intern

Computer Science / Data Science Intern

GrowTech Industries, LLC • Goodyear, AZ, US
[job_card.variable_days_ago]
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  • [job_card.full_time]
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Job Description

Job Description

Computer Science / Data Science Intern – Manufacturing Systems & Analytics

Location : Goodyear, AZ (On-Site)

Schedule : 20–40 hours per week

Employment Type : Internship / Co-Op (Paid)

About GTI Fabrication

GTI Fabrication is investing heavily in manufacturing systems, data visibility, and operational analytics. This role supports the intersection of software, data, and manufacturing operations.

Role Overview

The Computer Science / Data Science Intern will support manufacturing analytics, systems integration, and reporting initiatives. This role works closely with operations, engineering, and business systems teams to turn raw production data into actionable insights.

Key Responsibilities

  • Support development of dashboards and reports for production, quality, and inventory metrics
  • Assist with data extraction, cleaning, and analysis from ERP / MES systems
  • Help automate manual reporting processes using scripts or tools
  • Support basic SQL queries and data modeling efforts
  • Participate in manufacturing systems improvement projects
  • Document system workflows and data definitions
  • Collaborate with engineering and operations teams to understand real-world data needs

Qualifications

  • Currently pursuing a degree in Computer Science, Data Science, Information Systems, or related field
  • Able to work at least 20 hours per week
  • Working knowledge of Python, SQL, or similar programming languages
  • Strong analytical and problem-solving skills
  • Interest in manufacturing systems, analytics, or industrial technology
  • Experience with Power BI, Tableau, or similar tools is a plus
  • What You’ll Gain

  • Real-world experience applying software and data skills in manufacturing
  • Exposure to ERP, MES, and operational data systems
  • Hands-on analytics projects tied to production outcomes
  • Mentorship from systems and operations leaders
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