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Tier-1 brand, mid-level generalist analytics role, and metro HQ location increase candidate competition.
Analytics skills transferable, but logistics domain knowledge moderately increases specialization.
Explicit 3–5 years requirement plus mandatory Python, Spark and Azure Databricks skills make filters strict.
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Analyze complex operational data to identify improvement opportunities and deliver actionable insights for operations and business decisions.
Develop and implement scalable analytical models and data-driven solutions using Python, SQL, Spark/PySpark, and Azure Databricks to optimize operational productivity and cost effectiveness.
Establish and monitor operational KPIs, create dashboards and reports, support regional and head office teams, and deploy predictive/advanced analytics solutions to drive operational excellence.
Bachelor's or Master's degree in Data Science, Analytics, or Statistics.
3-5 years of experience in data analytics, preferably in supply chain, logistics, transportation, or operations domains.
Proficiency in Python, SQL, Spark/PySpark, and Azure Databricks required.
Travel requirement up to 25%; notice period not explicitly mentioned.
Experienced in supply chain or logistics analytics with a track record of building scalable data solutions and predictive models.
Strong technical orientation with hands-on expertise in advanced analytics tools and ability to translate large datasets into business insights.
Capable of collaborating with regional and head office teams to deliver timely, data-driven decision support under defined SLAs.