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Statistical Process Control Engineer Jobs in Des Moines, IA

... teams in engineering, design, project management, field service, plant operations, professional ... processes. • General understanding of equipment fabrication, troubleshooting, operation ...

... teams in engineering, design, project management, field service, plant operations, professional ... processes. • General understanding of equipment fabrication, troubleshooting, operation ...

Quality Engineer I

Des Moines, IA · On-site

$66K - $86K/yr

Lead Continuous Process Improvement activities throughout the organization. Manage creation of ... Conduct and organize training of employees on ISO 9001, statistical techniques, problem solving ...

Engineer, Automation & Controls

Newton, IA · On-site

$76K - $99K/yr

Directs, coordinates, and exercises functional authority for planning, organization, control ... Ability to work with mathematical concepts such as probability and statistical inference, and ...

Engineer, Automation & Controls

Newton, IA · On-site

$76K - $99K/yr

Directs, coordinates, and exercises functional authority for planning, organization, control ... probability and statistical inference, and fundamentals of plane and solid geometry and ...

... data processing and analysis. You will be responsible for developing and implementing data ... Statistics - Demonstrating proficiency in data engineering platforms like Databricks - Utilizing ...

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Statistical Process Control Engineer information

See Des Moines, IA salary details

$51.2K

$96.4K

$143.5K

How much do statistical process control engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for statistical process control engineer in Des Moines, IA is $96,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,700.00 and $113,700.00 per year, depending on experience, location, and employer.

What does a Statistical Process Control Engineer do?

A Statistical Process Control (SPC) Engineer is responsible for designing, implementing, and maintaining systems that monitor and control manufacturing processes using statistical methods. They analyze data to identify trends, reduce process variation, and improve product quality. SPC Engineers work closely with production teams to ensure processes remain stable, efficient, and in compliance with industry standards. Their role often involves training staff in SPC techniques and troubleshooting quality issues using data-driven approaches.

What are the key skills and qualifications needed to thrive as a Statistical Process Control Engineer, and why are they important?

To thrive as a Statistical Process Control Engineer, you need a solid background in statistics, process engineering, and quality management, often supported by a degree in engineering or a related field. Familiarity with SPC software (such as Minitab or JMP), Six Sigma methodologies, and quality system certifications like ASQ are typically required. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and collaborating with cross-functional teams. These skills and qualifications are vital to maintain product quality, optimize processes, and drive continuous improvement within manufacturing or production environments.

What is the difference between Statistical Process Control Engineer vs Quality Engineer?

AspectStatistical Process Control EngineerQuality Engineer
Primary FocusMonitoring and controlling manufacturing processes using statistical methodsEnsuring overall product quality through testing, inspection, and process improvements
CertificationsSix Sigma, Statistical Process Control (SPC) certificationsSix Sigma, Quality Management certifications (e.g., CQE)
Work EnvironmentManufacturing plants, process development labsQuality departments, production facilities
Industry UsageManufacturing, automotive, electronicsManufacturing, healthcare, aerospace

While both roles focus on improving product quality, the Statistical Process Control Engineer specializes in using statistical tools to monitor and control manufacturing processes, whereas the Quality Engineer oversees broader quality assurance activities, including testing and compliance. Understanding these differences helps in choosing the right career path or job search focus.

How does a Statistical Process Control Engineer typically collaborate with production and quality teams to drive process improvements?

A Statistical Process Control Engineer regularly works alongside both production and quality assurance teams to identify trends, troubleshoot issues, and implement data-driven improvements. They analyze real-time data from manufacturing processes, facilitate root cause analysis sessions, and communicate findings through reports or presentations. Collaboration often includes training team members on SPC tools and methodologies, as well as guiding them in using statistical techniques to monitor and control process variability. This cross-functional teamwork ensures that process adjustments are both technically sound and operationally practical, leading to sustained quality improvements.
What are popular job titles related to Statistical Process Control Engineer jobs in Des Moines, IA? For Statistical Process Control Engineer jobs in Des Moines, IA, the most frequently searched job titles are:
What job categories do people searching Statistical Process Control Engineer jobs in Des Moines, IA look for? The top searched job categories for Statistical Process Control Engineer jobs in Des Moines, IA are:
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

West Des Moines, IA • On-site

$74K/yr

Other

Posted 6 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

235th of 692 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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