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High—metro location, common data analyst title, and broad technical skillset increase candidate competition.
High—deep retail domain expertise and retail-specific KPIs limit cross-industry transferability.
High—explicit 7–10 years plus required retail domain expertise and analytics tool proficiency.
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Drive data-driven decisions across retail business functions including merchandising, supply chain, store operations, and e-commerce by translating business problems into analytical frameworks.
Analyze large datasets to identify trends and root causes affecting sales, inventory, pricing, and customer behavior, providing actionable recommendations to improve revenue and operational efficiency.
Develop and maintain dashboards and reports tracking key retail KPIs, support advanced analytics initiatives like demand forecasting and customer segmentation, and collaborate with stakeholders including senior leadership and data science teams.
7-10 years of experience as a data analyst in the retail domain.
Strong proficiency in SQL and Excel; experience with data visualization tools such as Power BI or Tableau is mandatory; working knowledge of Python or R is preferred.
Bachelor’s or master’s degree in engineering, Statistics, Economics, or a related field.
Location requirement: Bengaluru, India.
Experienced in omnichannel retail environments with a strong understanding of retail operations, merchandising, assortment planning, supply chain, and pricing.
Capable of bridging business, technology, and analytic teams to influence decision-making through data storytelling and presentation to senior leadership.
Comfortable managing large datasets and data warehouses, with exposure to advanced analytics or AI/ML use cases in retail.