Responsibilities:

• Analyze performance & translate data to e.g productivity/efficiency/utilization/loss drivers/improvement)
• Develop structured analytical models that explain performance changes.
• Define calculation logic, assumptions, and data definitions used in operational finance analysis.
• Support performance and improvement discussions with fact-based, data-driven insights.
• Analysis and modeling of operational, machine, and process data.
• Contribute to diagnostic and root cause analysis models, such as loss trees, driver decomposition etc.
• Work with other teams to ensure machine and process data is structured and analytically usable.
• Design structured datasets and data models that can be reused consistently across teams and sites.
• Contribute to data architecture design, including data flows, transformation layers, and semantic models.
• Develop analytics and data processing logic using R, Python, and SQL.
• Create and maintain clear documentation for data models, assumptions, calculation logic.
• Degree in Finance, Accountancy, Economic, Business (Fresh grad)
• Able to commit frequent traveling

Interested applicants, send in your updated resume by clicking “Apply Now”.

Lin Weikang
EA Personnel No: R21102570
EA License No: 23C1894