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Tier-1 brand, popular generalist role, metro location, and broad skillset requirements increase competition.
Core analytical and SQL skills transfer across industries, though retail domain experience is a moderate advantage.
Explicit years range plus mandatory SQL, BI, cloud and analytics skills make shortlisting stringent.
Execute data analyses supporting merchandising and various business domains using established methodologies.
Develop and maintain reports, dashboards, and basic predictive and diagnostic models to track performance and trends.
Collaborate with senior analysts, stakeholders, and data engineering teams to prepare data, run analyses, validate pipelines, and communicate findings clearly.
2-6 years overall experience; relevant experience 1-3 years.
Bachelor's degree: B.Tech/B.E. or Masters in Statistics/Econometrics/Mathematics (TI) or equivalent Bachelor's (US).
Proficiency in SQL, BI visualization tools (e.g., Power BI, Looker, Tableau), and experience with structured and unstructured databases including Hadoop and GCP BigQuery.
Experience with analytical techniques like regression, time-series, classification, and familiarity with Python, R, or Hive.
Experienced in data analytics within retail, merchandising, or marketing domains, with operational knowledge of large-scale data platforms and AI-assisted workflows.
Capable of working in fast-paced, collaborative environments, effectively partnering with business and technical teams to deliver actionable insights.
Familiar with modern data engineering practices, agile workflows, version control (Git), and applying foundational predictive analytics and AI tools to automate and enhance analysis productivity.