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# Manufacturing Engineer II (Integration) - Data Scientist

- **Company:** JMJ Phillip Group
- **Location:** United States
- **Experience:** Experienced
- **Salary:** $85,000.0 - $95,000.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Data Analysis, Databases, R (Programming Language), Python (Programming Language), MATLAB, SQL Databases, Data Streaming, Systems Integration, Technical Data Management Systems, Data Analytics, Enterprise Integration
- **Published:** September 2, 2026
- **Apply:** https://jmjphillip.com/jobs/2025/08/15/manufacturing-engineer-ii-integration-data-scientist/

## About the Role

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., * 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

## Description

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


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