Intern - DOE Characterization Engineering

About the Company

At WD, our vision is to power global innovation and push the boundaries of technology to make what you thought was once impossible, possible. At our core, WD is a company of problem solvers. People achieve extraordinary things given the right technology. For decades, we've been doing just that—our technology helped people put a man on the moon and capture the first-ever picture of a black hole.

We offer an expansive portfolio of technologies, HDDs, and platforms for business, creative professionals, and consumers alike under our Western Digital®, WD®, and WD_BLACK™. We are a key partner to some of the largest and highest-growth organizations in the world. From enabling systems to make cities safer and more connected, to powering the data centers behind many of the world's biggest companies and hyperscale cloud providers, to meeting the massive and ever-growing data storage needs of the AI era, WD is fueling a brighter, smarter future.

Responsibilities

Data Analysis & Engineering

• Perform engineering data analysis to identify trends, anomalies, and process insights from large-scale manufacturing or product datasets
• Apply statistical methods (including DOE principles) to support process characterization and optimization
• Translate data findings into actionable engineering recommendations

Data Mining & Automation

• Develop scripts and tools to automate repetitive data collection, processing, and reporting workflows
• Mine structured and unstructured datasets to uncover patterns relevant to product quality and process performance
• Build and maintain dashboards for real-time process monitoring and KPI tracking

Project Execution

• Execute assigned engineering projects end-to-end: scoping, data collection, analysis, and reporting
• Collaborate cross-functionally with Process, Quality, and Product Engineering teams
• Present findings and progress updates to engineering stakeholders in a clear and concise manner

Qualifications

Required:

• Currently pursuing a Master's degree in Electronics and Communication Engineering, Data Science, Computer Science, Computer Engineering, or Information Technology
• Basic understanding of statistical concepts (e.g., regression, hypothesis testing, ANOVA)
• Hands-on experience with data analysis or programming projects (academic or personal)

Preferred:

• Good English proficiency (written and verbal) for cross-functional and global team communication
• Programming skills: Python (data manipulation, automation, visualization using pandas, numpy, matplotlib, seaborn)
• Power BI (dashboard creation and data storytelling)
• Familiarity with SQL or data query languages
• Exposure to DOE, Six Sigma, or Lean methodologies is a plus
• Experience with JMP or Minitab for statistical analysis is advantageous