P2 Administrator

Job Summary

P2/SAP/BI maintain, data analysis, support WCM manager in factory. 

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. 

Education and Experience 

• Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Industrial Engineering, Operations Research, Automation, or related fields. 

• Minimum 2 years of data analysis experience in manufacturing or industrial sectors, with exposure to production workflows, equipment data, or supply chain management. 

• Experience in smart manufacturing (Industry 4.0), IoT, or digital factory initiatives is highly desirable. 

• Familiarity with manufacturing data characteristics (e.g., time-series data, high-dimensional data, unstructured data). 

• Awareness of data governance and security protocols. 

Relevant Academic Disciplines 

• Core Disciplines : Data Science, Computer Science, Applied Mathematics, Industrial Engineering. 

• Complementary Disciplines : Mechanical Engineering (digitalization focus), Automation (data analytics applications), Supply Chain Management (data-driven focus). 

Preferred Qualifications 

• Certifications in manufacturing data analytics (e.g., CPDA, CDMP) or Six Sigma Green Belt/Black Belt. 

• Hands-on experience in projects such as production scheduling optimization, predictive maintenance, or energy consumption analysis.