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Strong brand, metro Bangalore, mid-level generalist analytics role with broad skills increases applicant density.
Analytics and SQL skills transfer broadly, but retail/merchandising experience and GenAI needs increase specificity.
Explicit 5–8 years and mandatory SQL/BigQuery/BI/ML/GenAI requirements create strict screening filters.
Collaborate with business leaders to translate data into actionable insights supporting strategic decisions across multiple domains including Marketing, Supply Chain, and Finance.
Develop, deliver, and maintain analytical and AI-driven solutions using advanced techniques such as causal, predictive, prescriptive analytics, and Generative AI to support forecasting, optimization, and automation.
Manage large-scale datasets and build reliable data pipelines; ensure analytical outputs are accurate, scalable, and effectively communicated to non-technical stakeholders.
Overall 5-8 years of experience with 3-5 years relevant experience in data analytics or related roles.
Bachelor's or Master's degree in quantitative fields such as B.Tech/B.E., Statistics, Econometrics, Mathematics, Data Science, or Computer Science.
Strong hands-on expertise in SQL, SQL optimization, and data warehouse/business intelligence concepts; proficiency with BI visualization tools like Power BI, Looker, or Tableau.
Hands-on experience in R, Python, Hive, or other open-source languages; experience working with large datasets and platforms such as GCP BigQuery, Spark, Hadoop HDFS, and building data pipelines using orchestration tools like Airflow.
Proven ability to partner with business stakeholders to define analytic requirements, deliver insights, and influence decisions using data storytelling skills.
Experience integrating advanced analytics and AI (including Generative AI and LLM-based solutions) into analytical workflows to automate insights and improve productivity.
Background in retail, merchandising, or marketing analytics with strong technical expertise in data platforms and coding, capable of managing end-to-end analytics projects in fast-paced environments.