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EXL Linkedin · Posted 2d ago

Retail Business Analyst

India

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Role Overview

We are looking for a Retail Data & Analytics senior Analyst to support data-driven decision-making across accounts. The ideal candidate will have strong knowledge of retail/e-commerce data, hands-on experience with Databricks and Power BI, and an intermediate understanding of Data Science and statistical modelling.


The role will involve working with large and complex datasets to identify customer, product and trading insights, develop analytical solutions, and create dashboards that enable business stakeholders to make informed decisions.


Key Responsibilities

  • Analyze retail and e-commerce data to identify trends, customer behaviours and commercial opportunities.
  • Work with key retail metrics and datasets including:
  • Customer and product basket analysis
  • Sessions, visits and conversion funnels
  • Product views and product performance
  • Add-to-basket and checkout behaviour
  • Conversion rate and abandonment
  • Average Order Value (AOV)
  • Units per transaction
  • Customer purchase and retention behaviour
  • Sales, revenue and margin
  • Returns and cancellations
  • Product/category/brand performance
  • Build and maintain Power BI dashboards and reports for business and senior stakeholders.
  • Use Databricks to access, transform and analyse large-scale datasets.
  • Work with SQL and other analytical techniques to extract, transform and validate data.
  • Partner with Data Science teams to support predictive modelling, segmentation, recommendation, forecasting and experimentation initiatives.
  • Apply intermediate Data Science concepts including:
  • Statistical analysis
  • Hypothesis testing
  • Regression and classification
  • Customer segmentation
  • Feature engineering
  • Model evaluation and interpretation
  • A/B testing and experimentation
  • Translate business questions into analytical requirements and provide clear, actionable insights.
  • Work closely with Web Analytics, Data Science, BI and commercial teams to ensure consistency of data definitions and metrics.
  • Support data quality, validation and documentation of key retail metrics and datasets.
  • Present findings and recommendations clearly to both technical and non-technical stakeholders.


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