Engineer Intern

Job Duties

• Analyze historical hull wall thickness data to identify trends, high-risk areas, and key sources of variation.
• Develop data visualizations and summary reports (e.g., control charts, histograms, heatmaps) to communicate findings to Quality and Production teams.
• Design experiments (DOE) and structured trials to test hypotheses related to thickness variation and/or weakness; support execution on the manufacturing floor.
• Partner with Engineering, Production, and Quality to define critical-to-quality measurement locations, sampling plans, and acceptance criteria.
• Help develop and improve tools and workflows for capturing wall thickness data during production (templates, digital forms, databases, or dashboards).
• Support measurement system and data integrity improvements (gauge setup, data entry checks, basic MSA concepts).
• Participate in problem-solving activities (root cause analysis, corrective actions) to reduce thickness-related defects and improve process capability.

Minimum Qualifications:

• Currently pursuing a Bachelor's degree in Mechanical, Industrial, Manufacturing, Chemical Engineering, Materials Science, or a related Engineering/Engineering Technology program.
• Strong interest in quality engineering, manufacturing processes, and continuous improvement.
• Comfortable working with data: organizing datasets, performing basic statistical analysis, and drawing conclusions from evidence.
• Proficient in Microsoft Excel (pivot tables, charts); familiarity with Minitab, JMP, Python, or similar tools is a plus.
• Ability to work on the shop floor and learn measurement techniques (e.g., ultrasonic thickness gage or similar) with attention to detail.
• Strong communication and organizational skills; able to document work clearly and present results to cross-functional teams.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications:

• Coursework or experience with SPC/control charts, capability analysis, and basic Design of Experiments (DOE).
• Exposure to root cause analysis methods (5-Why, fishbone) and corrective/preventive action.
• Experience with data collection systems or dashboards (SharePoint/Forms, Power BI, SQL) and improving data integrity.