Data Quality Analyst - Intern

Marlborough, MA, US • Posted 2 days ago • Updated 10 hours ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Data Quality
  • Photonics
  • Optical Fiber
  • Lasers
  • Operational Efficiency
  • Testing
  • Quality Management
  • ROOT
  • Documentation
  • Corrective And Preventive Action
  • Auditing
  • Collaboration
  • Research and Development
  • Supply Chain Management
  • Trend Analysis
  • Reporting
  • Dashboard
  • Visualization
  • Leadership
  • Data Science
  • Statistics
  • Computer Science
  • Physics
  • Microsoft Excel
  • Pivot Table
  • Python
  • R
  • SQL
  • Microsoft Power BI
  • Analytical Skill
  • Conflict Resolution
  • Problem Solving
  • Attention To Detail
  • Organized
  • Effective Communication
  • Statistical Process Control
  • Minitab
  • JMP
  • Lean Six Sigma
  • Root Cause Analysis
  • Data Visualization
  • Reliability Engineering
  • Data Analysis
  • Manufacturing
  • Continuous Improvement

Summary

About IPG Photonics

IPG Photonics is the world leader in high-performance fiber lasers and photonic solutions used in manufacturing, medical, scientific, and communications applications. The Quality organization ensures that IPG products meet rigorous design, reliability, and performance standards. As a Quality Data Analyst Coop, you will play a key role in helping the team make data driven decisions to improve product quality and operational efficiency.

Position Summary

The Quality Data Analyst Co-op will support the Quality department by collecting, analyzing, and interpreting data generated from manufacturing processes, testing operations, and customer feedback. This role is ideal for a student pursuing a technical or engineering degree with strong analytical skills and an interest in quality systems, data analytics, and continuous improvement.

Key Responsibilities

  • Extract, clean, and analyze quality related datasets from manufacturing, test, and service systems.
  • Create dashboards, charts, and visual reports to identify trends, anomalies, and root causes.
  • Support investigation and troubleshooting efforts for nonconformities, yield issues, and process deviations.
  • Maintain and update quality documentation, reports, and records.
  • Support quality engineers with data preparation for corrective and preventive actions (CAPA), 8D reports, and internal audits.
  • Collaborate with cross functional teams (Manufacturing, R\&D, Test, Supply Chain) to gather data and communicate findings.
  • Recommend data driven improvements to enhance product quality and operational metrics.

Data Visualization Responsibilities (Integrated)

  • Develop clear, insightful data visualizations to support quality investigations, trend analysis, and reporting.
  • Build and maintain dashboards using tools such as Excel, Power BI, or other industry standard visualization libraries.
  • Transform large, complex datasets into user-friendly charts, graphs, and layouts that help engineers and leadership quickly understand issues and performance.
  • Present visual findings during team meetings and help communicate quality metrics to cross functional stakeholders.
  • Ensure consistency in formatting, labeling, and visual standards across recurring quality reports.

Required Qualifications

  • Currently pursuing a degree in Engineering, Data Science, Statistics, Computer Science, Physics, or a related field.
  • Proficiency with Excel (pivot tables, functions, charts); experience with Python, R, SQL, or Power BI is a plus.
  • Strong analytical and problem-solving abilities.
  • Ability to interpret data, draw conclusions, and present results clearly.
  • Detail-oriented, organized, and able to handle multiple tasks.
  • Effective communication skills and ability to work in a team environment.

Preferred Skills

  • Experience using statistical tools (SPC, Minitab, JMP, or similar).
  • Familiarity with quality methodologies (Lean, Six Sigma, Root Cause Analysis).
  • Exposure to manufacturing environments or complex electro-optical systems.
  • Understanding of data visualization tools or dashboarding.

Learning Outcomes

By the end of the co-op, the student will gain experience with:
  • Real-world quality and reliability engineering and data analytics.
  • Statistical methods used in high-tech manufacturing.
  • Working cross-functionally in a fast-paced engineering environment.
  • Using data to support continuous improvement and reliability initiatives.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10109239
  • Position Id: c1eaf41a5031964eb85021eb14e285f1
  • Posted 2 days ago
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