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Strong Tier-1 brand, metro location, popular data role, and broad required skills increase applicant competition.
Core analytics and pipeline skills are transferable, though retail domain experience moderately matters.
No explicit years but multiple mandatory platforms and advanced analytics requirements raise filter strictness.
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Lead application of data analytics and AI to influence merchandising strategy and business outcomes.
Translate ambiguous business problems into structured analytical approaches; design and deliver AI-driven solutions for decision support, forecasting, and automation.
Work with large-scale datasets using tools like GCP BigQuery, Spark, SQL, and maintain data pipelines; evaluate AI workflows and communicate insights effectively to business stakeholders.
Work Experience Required: Not explicitly mentioned in the JD
Experience with advanced analytics techniques including causal, predictive, and prescriptive analytics.
Hands-on experience with data platforms such as GCP BigQuery, Spark, SQL-based data warehouses, and data pipeline orchestration tools like Airflow.
Knowledge of responsible AI practices including data privacy, bias mitigation, and explainability.
Proven ability to independently handle ambiguous business problems and translate them into analytical solutions with measurable impact.
Strong technical skills combined with business acumen to partner effectively with stakeholders and influence executive decision-making.
Experience working in fast-moving, high-impact environments with large-scale retail or e-commerce data analytics applications.