Senior Statistical Process Control Analyst
Listed on 2026-07-27
-
Engineering
Quality Engineering -
Quality Assurance - QA/QC
Quality Engineering
A DAY IN THE LIFE
This position supports Blattner's Continuous Improvement team throughout the full DMAIC lifecycle. Most of this role's time is spent mining and analyzing production, safety, quality, and cost data to identify root causes, quantify opportunities, and validate whether an improvement worked during the Define, Measure, Analyze, and Improve phases. Once improvement is proven and a project moves into the Control phase, this role is hyper-focused on building and maintaining the statistical infrastructure (control charts, capability studies, and control plans) that lets the gain hold.
Beyond the analysis itself, this role is accountable for value realization (confirming projected savings materialize), improvement sustainment (making sure gains hold well after a project closes), and operational integration (embedding control charts and dashboards into how project teams already work). This includes owning the Continuous Improvement data dashboard, building infrastructure that helps teams understand and manage risk in their decision environment, and standardizing how the organization reports on operational cost effectiveness.
This is an individual contributor role that provides analytical and statistical rigor in support of the Continuous Improvement team, who lead and facilitate improvement efforts directly with project teams and stakeholders.
This position supports Blattner's Continuous Improvement team throughout the full DMAIC lifecycle. Most of this role's time is spent mining and analyzing production, safety, quality, and cost data to identify root causes, quantify opportunities, and validate whether an improvement worked during the Define, Measure, Analyze, and Improve phases. Once improvement is proven and a project moves into the Control phase, this role is hyper-focused on building and maintaining the statistical infrastructure (control charts, capability studies, and control plans) that lets the gain hold.
Beyond the analysis itself, this role is accountable for value realization (confirming projected savings materialize), improvement sustainment (making sure gains hold well after a project closes), and operational integration (embedding control charts and dashboards into how project teams already work). This includes owning the Continuous Improvement data dashboard, building infrastructure that helps teams understand and manage risk in their decision environment, and standardizing how the organization reports on operational cost effectiveness.
This is an individual contributor role that provides analytical and statistical rigor in support of the Continuous Improvement team, who lead and facilitate improvement efforts directly with project teams and stakeholders.
THE ROLE
- Mines and analyzes production, quality, safety, and cost data to identify root causes and candidate opportunities, providing the data sources each Continuous Improvement team member needs for their assigned projects.
- Develops infrastructure that helps Continuous Improvement teams better understand and manage risk in their decision environment to capture opportunities.
- Partners with the Continuous Improvement team during the Measure and Analyze phases to establish statistically sound baselines and quantify opportunity size using hypothesis testing (t-tests, chi-square, ANOVA) and regression analysis.
- Validates measurement systems (Gage R&R) to confirm data is reliable before it's used for analysis or control limits and identifies areas across the organization where data accuracy needs improvement.
- Designs and maintains control charts (X-bar/R, p-charts, c-charts, etc.) and conducts process capability studies (Cp/Cpk, Pp/Ppk), remaining hyper-focused on the Control phase of DMAIC.
- Bachelor's degree in Statistics, Industrial Engineering, Data Science, Mathematics, or a related quantitative field; or equivalent combination of education and experience.
- Two or more years of experience in data analysis, statistical analysis, or continuous improvement, preferably within a construction, energy, or industrial environment.
- A Lean Six Sigma Green Belt certification is preferred and/or…
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