JMJ PHILLIP
Manufacturing Engineer II (Integration) – Data Scientist
JMJ PHILLIP, Perrysburg, Ohio, us, 43552
We are seeking a detail-oriented and innovative Manufacturing Engineer II (Integration) – Data Scientist to support manufacturing operations by integrating data-driven solutions that enhance production efficiency, quality, and reliability. This role is ideal for a professional with a passion for leveraging data analytics and engineering expertise to optimize manufacturing processes.
Position Responsibilities
Data Analysis and Process Optimization Collect, analyze, and interpret manufacturing data to identify trends, inefficiencies, and improvement opportunities Develop data models and algorithms to support predictive maintenance, quality control, and process optimization System Integration Implement integration solutions between manufacturing systems, databases, and analytical tools Collaborate with cross-functional teams to ensure seamless data flow and system compatibility Continuous Improvement Recommend and implement process improvements using Lean, Six Sigma, and other best practices Monitor the performance of implemented solutions to ensure long-term effectiveness Prerequisites
Bachelor’s degree in Manufacturing Engineering, Data Science, Industrial Engineering, or related field 3–5 years of experience in manufacturing engineering with a focus on data analysis or integration Proficiency in data analytics tools such as Python, R, SQL, or MATLAB Strong understanding of manufacturing systems, automation, and process improvement methodologies Certifications (Preferred, but not Required)
Lean Six Sigma Certification Certified Manufacturing Engineer (CMfgE) Data Science or Analytics Certification What the Role Offers
Salary Range: $85,000 – $95,000 Competitive compensation package Comprehensive benefits plan Opportunities to work on cutting-edge manufacturing and data integration projects A collaborative work environment focused on innovation and continuous improvement Why Perrysburg?
Perrysburg offers a strong manufacturing base with access to skilled talent and advanced production facilities. The community provides a balance of professional opportunities and quality of life, making it an attractive location for engineering and technical professionals.
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Data Analysis and Process Optimization Collect, analyze, and interpret manufacturing data to identify trends, inefficiencies, and improvement opportunities Develop data models and algorithms to support predictive maintenance, quality control, and process optimization System Integration Implement integration solutions between manufacturing systems, databases, and analytical tools Collaborate with cross-functional teams to ensure seamless data flow and system compatibility Continuous Improvement Recommend and implement process improvements using Lean, Six Sigma, and other best practices Monitor the performance of implemented solutions to ensure long-term effectiveness Prerequisites
Bachelor’s degree in Manufacturing Engineering, Data Science, Industrial Engineering, or related field 3–5 years of experience in manufacturing engineering with a focus on data analysis or integration Proficiency in data analytics tools such as Python, R, SQL, or MATLAB Strong understanding of manufacturing systems, automation, and process improvement methodologies Certifications (Preferred, but not Required)
Lean Six Sigma Certification Certified Manufacturing Engineer (CMfgE) Data Science or Analytics Certification What the Role Offers
Salary Range: $85,000 – $95,000 Competitive compensation package Comprehensive benefits plan Opportunities to work on cutting-edge manufacturing and data integration projects A collaborative work environment focused on innovation and continuous improvement Why Perrysburg?
Perrysburg offers a strong manufacturing base with access to skilled talent and advanced production facilities. The community provides a balance of professional opportunities and quality of life, making it an attractive location for engineering and technical professionals.
#J-18808-Ljbffr