ESSENTIAL DUTIES AND 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
REQUIRED: Currently pursuing a Master's degree in: Data Science Computer Science Computer Engineering 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 (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
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