Retail Inventory Analytics Lead — AI & Optimization

MR. D.I.Y. Trading Sdn. Bhd. (M); Selangor; On-site; MYR 60,000 - 100,000; Full time

Job summary

MR. D.I.Y. Trading Sdn. Bhd. (M) in Selangor seeks a Data Analyst Executive to tackle complex retail inventory, replenishment, and allocation challenges across stores and warehouses.

You will own the analytics lifecycle from problem framing to validation, create insights using SQL, Python/pandas, Excel and BI tools, and present findings to diverse audiences while driving productivity via automation and AI-assisted tools.

Qualifications

• Bachelor's degree or above in Data Analytics, Data Science, Statistics, Mathematics, Computer Science, Business Analytics, Engineering, Economics or related fields.

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.

Skills

SQL

Python/pandas

Excel

Power BI

Looker Studio

Education

Bachelor's Degree or above in a related data field

Tools

Power BI

Looker Studio

Job description

MR. D.I.Y. Trading Sdn. Bhd. (M) in Selangor seeks a Data Analyst Executive to tackle complex retail inventory, replenishment, and allocation challenges across stores and warehouses.

You will own the analytics lifecycle from problem framing to validation, create insights using SQL, Python/pandas, Excel and BI tools, and present findings to diverse audiences while driving productivity via automation and AI-assisted tools.