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Entry LevelFull-timePythonGitAI
Salary Range
$11,220 - $15,180 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are seeking a Process Engineering Engineer to use data analytics and engineering principles to improve manufacturing performance. This role focuses on analyzing operational data, building dashboards, supporting automation and AI initiatives, and working with cross-functional teams to solve problems, optimize processes, and drive data-driven decisions.
Key Responsibilities
- →Analyze manufacturing, process, and operational data to identify trends, inefficiencies, and improvement opportunities using tools such as Python, SQL, Power BI, JMP, and Minitab.
- →Develop, maintain, and enhance data dashboards, reports, and visualizations to support data-driven decision-making across engineering and operations teams.
- →Support automation, digitalization, and AI-driven initiatives by designing, testing, and implementing analytical models, scripts, or tools.
- →Collaborate with cross-functional teams (engineering, manufacturing, quality, IT) to understand business requirements and translate them into technical and analytical solutions.
- →Perform root cause analysis and structured problem-solving for process, quality, or system-related issues using statistical and analytical methodologies.
- →Conceptualize and propose practical, scalable solutions to complex or ambiguous problems, balancing short-term execution with long-term strategic impact.
- →Assist in optimizing manufacturing processes, yield, reliability, or system performance through data analysis and continuous improvement initiatives.
- →Communicate findings, insights, and recommendations clearly and concisely to both technical and non-technical stakeholders through presentations, reports, and documentation.
- →Apply fundamental engineering and technical concepts to support troubleshooting, system analysis, and decision-making.
- →Ensure data accuracy, integrity, and proper documentation of analytical methods, assumptions, and results.
- →Continuously enhance technical skills and stay updated on emerging technologies related to data analytics, automation, and AI.
