P2 Administrator

Job Summary

To apply and teach WCM knowledge and methodology to support the results in the respective factory, and work with and support WCM Manager and the pillar to achieve overall process and factory KPIs.

What you will do

Data Identification and Extraction

• Gain a deep understanding of enterprise operational systems (e.g., ERP, MES, SCADA) to identify critical business data types and requirements.
• Design and implement efficient data extraction models to optimize data collection processes, ensuring data integrity and accuracy.
• Extract structured and unstructured data from production, supply chain, equipment management, and other relevant systems.

Data Analysis and Modeling

• Develop data analysis models (e.g., predictive, diagnostic, optimization models) aligned with business needs to support production efficiency, cost control, quality improvement, and related scenarios.
• Utilize statistical analysis, machine learning, and visualization tools (e.g., Python, R, SQL, Tableau, Power BI) to derive actionable insights.
• Deliver periodic analytical reports to guide decision-making in production optimization, resource allocation, risk mitigation, and strategic planning.

Business Guidance and Collaboration

• Translate analytical findings into practical recommendations (e.g., production process enhancements, predictive maintenance strategies).
• Collaborate cross-functionally with production, engineering, and quality teams to drive data-informed process improvements.

WCM competence

• Apply the WCM knowledge and methodology, to support the business operation with WCM and data, achieve the performance.

We believe you have

Data Extraction and Processing Proficiency

• Expertise in SQL, Python, or similar tools, with hands-on experience in extracting, cleaning, and integrating complex datasets.
• Familiarity with API integration, database management, and ETL pipeline design.

Advanced Analytical and Modeling Skills

• Strong knowledge of statistics, machine learning algorithms (e.g., regression, clustering, time series forecasting), and libraries (e.g., Pandas, NumPy, Scikit-learn).
• Ability to translate business challenges into data-driven problems with logical rigor and solution-oriented thinking.

Manufacturing Industry Acumen

• Understanding of key manufacturing KPIs (e.g., OEE, equipment utilization rate, first-pass yield, inventory turnover rate).
• Knowledge of Lean Manufacturing, Six Sigma, or similar methodologies is a plus.

Communication and Stakeholder Engagement

• Ability to communicate technical insights effectively to non-technical stakeholders and drive collaborative action.

Technical Toolset

• Proficiency in BI tools (Tableau, Power BI); experience with manufacturing systems (e.g., SAP, Oracle) is preferred.