Inventory Analytics Analyst — SQL, Python & Dashboards

MR DIY Malaysia; Seri Kembangan; On-site; MYR 60,000 - 90,000; Full time

Job summary

MR DIY Malaysia is seeking a data analytics specialist to optimize inventory allocation and analyze store-SKU performance. You will write efficient SQL, clean and transform data with Python/pandas, and build PyQt tools to visualize store-level insights.

Responsibilities include creating Excel analyses and dashboards in PowerBI/Looker Studio, plus ad-hoc reporting and AI-driven productivity improvements while ensuring data confidentiality.

Qualifications

• SQL, Python/pandas, and PyQt skills; Machine Learning is a plus.
• Solid understanding of inventory planning concepts.
• Advanced Excel skills; experience with PowerBI/Looker Studio/BigQuery is a plus.
• Detail-oriented, problem solver, and able to work with large datasets.

Responsibilities

• Apply inventory planning logic to optimize inventory allocation.
• Analyze store-SKU performance, trigger orders, and replenishment models.
• Write and optimize SQL queries for aggregation and inventory analysis.
• Perform data cleaning, transformation, and analysis using Python/pandas.
• Develop PyQt tools to visualize and manage store-level data.
• Create and maintain Excel analyses and PowerBI/Looker Studio dashboards.
• Prepare ad-hoc reports to support decision-making.
• Leverage modern AI-driven analytical techniques to enhance productivity and insights in a responsible and confidential manner.

Skills

SQL

Python

Pandas

PyQt

Excel

PowerBI

BigQuery

Looker Studio

Education

Data Science / CS degree

Tools

Looker Studio

PowerBI

BigQuery

Job description

MR DIY Malaysia is seeking a data analytics specialist to optimize inventory allocation and analyze store-SKU performance. You will write efficient SQL, clean and transform data with Python/pandas, and build PyQt tools to visualize store-level insights.

Responsibilities include creating Excel analyses and dashboards in PowerBI/Looker Studio, plus ad-hoc reporting and AI-driven productivity improvements while ensuring data confidentiality.