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Statistical Engineering Jobs in Kokomo, IN (NOW HIRING)

Monitor and maintain all Statistical Process Control (SPC) * Conduct risk assessments to identify ... Bachelor's Degree in Engineering or Technology equivalent * Knowledge and experience in ...

Quality Engineer

Noblesville, IN · On-site

$67K - $87K/yr

... statistical process-control methods for engineering, production, and warehouse processes. · Coordinate resolution of customer product complaints. · Support the ISO 9001 based Quality System. · ...

Quality Engineer

Noblesville, IN

$67K - $87K/yr

... statistical process-control methods for engineering, production, and warehouse processes. · Coordinate resolution of customer product complaints. · Support the ISO 9001 based Quality System. · ...

Quality Engineer

Noblesville, IN · On-site

$67K - $87K/yr

... statistical process-control methods for engineering, production, and warehouse processes. • Coordinate resolution of customer product complaints. • Support the ISO 9001 based Quality System. • ...

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Engineer Lead

Noblesville, IN · On-site

$96K - $126K/yr

Support and understand statistical process-control methods for engineering, production, and warehouse processes. * Coordinate resolution of customer product complaints. * Support the ISO 9001 based ...

Quality Engineer

Noblesville, IN · On-site

$67K - $87K/yr

This role will primarily support R&D and Process Engineering activities to ensure compliance with ... Provide guidance on the use of statistical techniques for selection of sampling strategies and ...

Bachelor of Science degree in Chemical, Mechanical or Electrical Engineering from an ABET ... SPC (Statistical Process Control) * Experience with quality certification and system such as ...

Quality Engineer

Kokomo, IN · On-site

$62K - $81K/yr

S. in Engineering or 1-3+ years w/ M.S. or higher; experience in Manufacturing and/or Quality ... and Statistical Process Control (SPC) (All P); Knowledge of thermo-mechanical and/or melting ...

Collects data and performs statistical analysis. Maps and documents processes. Independently ... Applies engineering methodologies/tools such as product slotting, studying labor standards (time ...

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Statistical Engineering information

What is statistical engineering?

Statistical engineering is an interdisciplinary field that focuses on the integration and application of statistical methods and principles to solve complex, large-scale problems in science, business, and engineering. It involves designing data collection processes, analyzing and interpreting data, and implementing statistical solutions within larger systems. Statistical engineers often work on projects that require collaboration with other engineering disciplines, using statistics as a foundational tool to drive decision-making and innovation.

How does a statistical engineer typically collaborate with cross-functional teams to implement data-driven solutions?

Statistical Engineers frequently work alongside data scientists, software engineers, and business analysts to design and implement robust data-driven solutions. They are responsible for translating complex statistical models into actionable insights and ensuring that these models are integrated effectively within existing systems. Collaboration often involves regular meetings to align on project goals, sharing progress updates, and troubleshooting technical challenges together. This interdisciplinary teamwork is essential for ensuring that statistical methodologies are not only theoretically sound but also practically applicable to real-world business problems.

What are the key skills and qualifications needed to thrive as a statistical engineer, and why are they important?

To thrive as a Statistical Engineer, you need strong quantitative analysis skills, a background in statistics or mathematics, and often a relevant degree such as in engineering or applied statistics. Proficiency with statistical software (e.g., R, SAS, Python), data management systems, and sometimes Six Sigma certification is typically required. Critical thinking, problem-solving, and clear communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These skills ensure accurate data-driven decisions, efficient process improvements, and effective solutions to complex engineering challenges.

What is the difference between Statistical Engineering vs Data Scientist?

AspectStatistical EngineeringData Scientist
Required credentialsStatistics, Data Analysis, EngineeringStatistics, Computer Science, Data Analysis
Work environmentManufacturing, R&D, Engineering teamsBusiness, Tech, Research sectors
Employer usageOptimizing processes, designing experimentsBuilding models, insights, predictive analytics

Statistical Engineering focuses on applying statistical methods to improve engineering processes and product development, often within manufacturing or R&D settings. Data Scientists analyze large datasets to extract insights, build predictive models, and support business decisions. While both roles require strong statistical skills, Statistical Engineering emphasizes process optimization and experimental design, whereas Data Scientists focus on data-driven insights across diverse industries.

What do statistical engineers do?

Statistical engineers develop and implement statistical models and methods to analyze complex data, often focusing on process improvement and quality control. They use tools like statistical software and programming languages such as R or Python and collaborate with data scientists and engineers to optimize systems and decision-making processes.

What cities near Kokomo, IN are hiring for Statistical Engineering jobs?

Cities near Kokomo, IN with the most Statistical Engineering job openings:

Process Engineer

StarPlus Energy

Kokomo, IN • On-site

Full-time

Re-posted 22 days ago


Job description

At StarPlus Energy, a joint venture between Samsung/Stellantis, join us in establishing the first plant of its kind in Indiana. As a member of our team, you will play an important role in our company's positive culture by helping us build and maintain an effective organization as the automotive industry moves toward an electric future.
The Process Engineer will develop and optimize the EV battery production process to improve safety, quality, productivity, and sustainability. The role will develop, monitor, analyze, and implement new processes, procedures, and equipment as needed.
ROLES AND RESPONSIBILITIES
  • Analyze and optimize productivity, yield, and Overall Equipment Efficiency (OEE)
  • Responsible for defect rate monitoring, improvement, and product sustainability in manufacturing
  • Lead product and process Continuous Improvement (CI) and development activities
  • Implement Factory Acceptance Test (FAT) & Site Acceptance Test (SAT) protocols
  • Enhance processes in battery manufacturing systems including the implementation of lean manufacturing, 5S, and Kaizen projects
  • Lead Cross-Function Team (CFT) based activities with Production and Maintenance to troubleshoot inefficiencies and optimize productivity
  • Analyze safety and quality issues to recommend corrective actions
  • Monitor and maintain all Statistical Process Control (SPC)
  • Conduct risk assessments to identify and eliminate potential defects
  • Create, maintain, and update various Standard Operating Procedures (SOP) to ensure all operators develop a full understanding of process changes
  • Collaborate with other departments to ensure smooth production flow between each process
  • Prepare for and participate in meetings between teams

Basic Qualifications:
  • Bachelor's Degree in Engineering or Technology equivalent
  • Knowledge and experience in manufacturing and Continuous Improvement
  • Knowledge of time studies, line balancing, lean manufacturing, bottleneck analysis, PFMEAs, and process controls
  • Excellent verbal and written communication
  • Excellent knowledge of Microsoft Office suite
  • Skilled in handling multiple projects simultaneously

Preferred Qualifications:
  • Experience in validation of needed equipment capacities, commissioning and ramp- up schedules
  • Proficient in application of statistical knowledge and tools such as Minitab or JMP
  • Experience in ERP systems, or equivalent
  • Working understanding of vision systems such as Keyence or Cognex
  • Knowledge of laser welding, CT & X-Ray scanning
  • Knowledge of electrode, notching, stacking, assembly, formation, or production processes pertaining to battery manufacturing