Bangkok, Thailand
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Listing record updated: October 9, 2026. We archive records after 60 days without an update. This date does not confirm that the employer is still hiring.
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This role transforms retail and pricing data into actionable business decisions by building and maintaining pricing intelligence products. The manager validates pricing recommendations and commercial data while partnering with Commercial, Finance, Operations, Data Science, and BI teams to drive measurable improvements in sales, margins, and operational performance. Responsibilities include classifying SKU-level pricing roles, maintaining decision-support tools like the Price Dashboard, and leading ad-hoc analyses across commercial topics. The position requires developing robust analytical models using SQL, BI tools, and Python to support pricing, promotion, and assortment decisions.
Classify and maintain SKU-level pricing roles, including Traffic Builder, KVI, EDLP, Promotion, and Normal Margin Builder, and apply Commercial-approved pricing logic.
Build, maintain, and improve the Price Dashboard, Focus Product Board, Price Index, margin views, and other decision-support tools; ensure agreed data freshness and accuracy.
Review and validate AI price-decision recommendations before they reach Commercial; identify anomalies, explain key drivers, and recommend appropriate actions.
Partner with the Data Science team on price elasticity, cross-elasticity, substitution, basket-impact, promotion, and markdown analysis.
Build margin-mix, price-change, and scenario simulations to support pricing, promotion, and assortment decisions.
Bachelor's degree or higher in Engineering, Economics, Statistics, Business, Finance, Supply Chain, Computer Science, or a related quantitative field.
2-5 years of experience in pricing, revenue management, commercial analytics, data analytics, business intelligence, or a related role.
Strong SQL skills; experience with Power BI or another BI tool. Python and Databricks SQL are preferred.
Ability to analyze large datasets, validate data quality, build repeatable analytical models, and present findings to business stakeholders.
Working knowledge of pricing, price elasticity, promotion effectiveness, margin, or retail commercial concepts; retail/FMCG experience is preferred.
Experience with forecasting or experimentation
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