Job Description – Statistical Quality Engineer
Position Summary
We are seeking a highly analytical and detail-oriented Statistical Quality Engineer to drive scrap reduction and process improvement initiatives across our manufacturing operations. This role is focused on using data to identify waste, perform capability studies, and support root cause investigations. The ideal candidate will have a strong statistical background, proficiency with data tools, and the ability to translate findings into actionable business decisions.
Key Responsibilities
- Collect, analyze, and report scrap and defect data; create Pareto analyses to prioritize issues.
- Develop capability studies (Cp, Cpk, Pp, Ppk) for machine processes and monitor process stability.
- Partner with production, engineering, and quality teams to identify cost-reduction opportunities through data.
- Drive automated and manual data collection from machine processes and inspection systems.
- Support root cause investigations with advanced statistical tools (DOE, regression, hypothesis testing).
- Recommend resource allocation (time, engineering focus, capital investment) based on highest ROI scrap reduction opportunities.
- Present clear dashboards, reports, and visualizations to management highlighting trends, risks, and progress.
- Maintain strong compliance with ISO, IATF, and customer quality requirements.
Qualifications
Bachelor’s degree in Statistics, Industrial Engineering, Quality Engineering, Data Analytics, or related field.3+ years of experience in manufacturing quality, process engineering, or data / statistical analysis.Strong knowledge of SPC, DOE, regression, ANOVA, hypothesis testing, and capability studies.Proficiency in statistical software (Minitab, JMP, or equivalent) and Excel / Power BI.Experience with root cause analysis tools (5 Why, Fishbone, FMEA, 8D).Ability to communicate complex data findings in clear, actionable terms.Hands-on mindset; comfortable engaging directly with operators, engineers, and quality teams.