×
Register Here to Apply for Jobs or Post Jobs. X

Senior Statistical Process Control Analyst

Job in Saint Paul, Ramsey County, Minnesota, 55199, USA
Listing for: Blattner
Full Time position
Listed on 2026-07-27
Job specializations:
  • Engineering
    Quality Engineering
  • Quality Assurance - QA/QC
    Quality Engineering
Salary/Wage Range or Industry Benchmark: 83109 - 120508 USD Yearly USD 83109.00 120508.00 YEAR
Job Description & How to Apply Below

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.

STEP INTO

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.
What You’ll Need
  • 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.
What Sets You Apart
  • A Lean Six Sigma Green Belt certification is preferred and/or…
Position Requirements
10+ Years work experience
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)
0
200
Filters
Education Level
Experience Level (years)
Posted in last:
Salary