The End of Line (EOL) Data Analyst & NVH Solution Set Developer is an entry-level to early-career role focused on using Minitab, Microsoft Excel, and structured data analysis to support the monitoring, analysis, and improvement of production end-of-line data systems. In this role, you will develop interim and permanent corrective action solution sets for complex noise, vibration, and harshness (NVH) challenges. You will partner with engineering, manufacturing, quality, calibration, validation, and plant operations teams to ensure EOL data is accurate, actionable, and effectively used to identify trends, resolve issues, and drive continuous improvement.

Key Responsibilities

• Develop data-driven interim and permanent corrective action solution sets for complex noise and vibration challenges based on EOL data trends, statistical analysis, NVH findings, root-cause inputs, and cross-functional engineering feedback.

• Monitor daily end-of-line test results, production data, and summary reports to identify statistically significant trends, recurring failure modes, population shifts, and emerging quality concerns.

• Translate EOL and NVH analysis into practical containment actions, test adjustments, process recommendations, issue-screening logic, and longer-term corrective action paths.

• Utilize Microsoft Excel and Minitab to analyze EOL test stand and production measurement datasets, emphasizing trend analysis, population comparisons, control charts, capability studies, and pass/fail performance.

• Perform basic to intermediate statistical analysis, including data sorting, filtering, pivot tables, summary statistics, distribution reviews, outlier checks, control limits, process capability, regression, and variation studies.

• Support the development and maintenance of dashboards, Excel-based trackers, Minitab studies, reports, and data visualization tools that communicate EOL performance to plant stakeholders.

• Assist with EOL limit setting and validation by reviewing population statistics, measurement variation, normality, capability, control chart behavior, false-fail risk, and pass/fail margins.

• Work with engineering and manufacturing teams to validate measurement outputs and support proper interpretation of EOL results.

• Provide timely analysis and supporting data during launch, production ramp-up, quality spills, audit findings, and issue resolution activities.

• Document analysis methods, reporting processes, lessons learned, and standard work for repeatable EOL data review.

Work Arrangement: On-site / Plant-facing - travel to plants is required

Basic Qualifications

• Associate degree in engineering technology, data analytics, computer science, manufacturing technology, statistics, or a related technical field (Bachelor’s degree preferred).

• 2+ years of experience working with manufacturing data, test data, quality data, production reporting systems, or a related technical environment.

• Strong Microsoft Excel skills (formulas, pivot tables, lookup functions, charting, conditional formatting, data cleanup, and repeatable report creation).

• Experience or coursework using Minitab for statistical analysis (control charts, process capability, distribution analysis, hypothesis testing, regression, and measurement system analysis).

• Ability to organize, analyze, and interpret technical data, recognize performance shifts, and summarize findings clearly for technical and non-technical audiences.

• Basic understanding of databases, data extraction, data manipulation, or structured reporting.

• Strong problem-solving skills, attention to detail, and ability to thrive in a fast-paced on-site plant environment.

• Valid driver’s license.

Preferred Qualifications

• Bachelor’s degree in engineering, data science, statistics, or computer science.

• Internship, co-op, or academic project experience using Excel, Minitab, MATLAB, or similar tools to analyze manufacturing, test, quality, or signal data.

• Exposure to Minitab analysis tools such as control charts, capability analysis, normality testing, regression, ANOVA, hypothesis testing, or Gage R&R.

• Basic knowledge of measurement systems, data acquisition, signal processing, or production test stand outputs (familiarity with Bauer systems is a plus).

• Familiarity with manufacturing execution systems, quality systems, EOL test software, or plant data architecture.

• Experience supporting root-cause investigations, technical problem solving, corrective action, or continuous improvement activities.