Data Analyst Executive (R&D - Analytic & Improvement)
Key Responsibilities:
Analyse complex retail inventory, replenishment and allocation problems involving stores, SKUs, stock, sales, warehouse supply, lead time, festivals and other business conditions.
Take ownership of analysis from problem understanding, data identification and validation through analysis, findings, recommendations and follow-up.
Use SQL, Python/pandas, Excel and BI tools to process, analyse and visualise large datasets.
Validate data and analytical result, cross-checking and reasonableness checks before using them for decisions.
Prepare clear reports and presentations, adapting explanations for different levels of technical knowledge.
Proactively identify issues, ask questions, challenge assumptions and bring ideas.
Leverage AI, automation and other suitable tools to improve productivity while understanding and validating the underlying logic and results.
Requirements:
Bachelor's Degree or above in Data Analytics, Data Science, Statistics, Mathematics, Computer Science, Business Analytics, Engineering, Economics or related fields.
Strong logical thinking, problem-solving ability and attention to detail.
Good foundation in SQL, Python/pandas and advanced Excel; experience with Power BI, Looker Studio or similar tools is an advantage.
Able to work with large datasets and understand data cleaning, transformation, validation and reconciliation.
Able to determine an appropriate analytical approach while discussing key directions with the superior.
Proactive and willing to ask questions, investigate unclear issues, challenge existing practices and contribute ideas.
Able to explain analytical methodology, assumptions and findings clearly to both technical and non-technical audiences.
Retail, inventory, replenishment or allocation knowledge is an advantage but not mandatory.
Experience with databases, Parquet, automation, AI-assisted tools, simulation or machine learning is an advantage.
Fresh graduates with strong analytical ability and relevant academic/internship projects are welcome.