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

Data Analyst (Graduate programme) @Woodlands