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Business Intelligence Manager

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Onsite

Business Intelligence Manager

CP AXTRA PUBLIC COMPANY LIMITED

Business Intelligence Manager

Skills

SQL QueriesE-commerce WebsitesTableauPythonData VisualizationRData AnalysisSupply ChainPower BI

16 hours ago

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Important information


Contract type:

Permanent

Location:

Bangkok, Thailand

Work mode:

Onsite

Published on:

27 October 2026

What they need


Key Responsibilities

·       Profit & Sales Management: Lead the development of advanced revenue, margin, and P&L diagnostic models. Provide data-driven guardrails and pricing optimization insights to maximize profitability across commercial retail categories.

·       Data Anomaly Tracking: Establish automated monitoring and alerting systems to detect real-time retail supply chain anomalies, including store/DC stock level variances, Out-of-Stock (OOS) patterns, and systemic inventory leakages.

·       Data Architecture & Analytics: Design, deploy, and maintain enterprise-grade BI dashboards (Tableau/Power BI) and predictive data structures, enabling commercial merchandising and strategy teams to make accurate data decisions autonomously.

Qualifications & Requirements

·       Target Industry Background: 3 to 7 years of intensive professional experience in Business Intelligence, Data Analytics, Commercial Finance, or Supply Chain Analytics within a Retail (E-commerce/Brick-and-Mortar) or FMCG environment. Prior experience directly managing high-volume retail P&L datasets, sales forecasting, and commercial metrics is essential.

·       Technical Proficiency: Expert-level mastery of SQL and professional data visualization suites (Tableau, Power BI). Advanced experience with Python or R for building statistical retail data modeling is highly preferred.

·       Dynamic Multi-tasking: Strong competency in prioritizing and executing multiple concurrent data analysis pipelines under tight business and promotional deadlines.

·       Resilience & Agility: A fast learner who adapts quickly to shifting data architectures, structural changes, and macro-retail trends, turning raw data into concrete commercial solutions.

·       Strong business acumen with an innate ability to connect granular data anomalies directly to broader financial impacts.

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