Data Scientist

Responsibilities

• Own and define the end-to-end Retail analytics strategy, including KPI framework design and insight delivery
• Lead the build and governance of dashboards and performance reporting across site, category, marketing, and operations
• Drive cohort analysis, customer segmentation, LTV modelling, and advanced funnel analytics
• Partner with data engineering teams to architect data pipelines and ensure data quality
• Manage and mentor a team of 2-3 junior analysts
• Design and oversee A/B tests, experiments, and quick-win initiatives to drive conversion and retention
• Present insights and strategic recommendations to senior leadership and cross-functional stakeholders
• Establish and govern data tracking infrastructure across all digital channels
• Identify root causes of underperformance in product availability, pricing, promotions, and retention

Requirements

• 5+ years of experience in Retail Analytics or Merchandising
• Advanced proficiency in SQL and Python or PySpark
• Deep knowledge of retail KPI frameworks (traffic, conversion, retention, LTV)
• Expertise in promo, pricing, and merchandising analytics
• Strong understanding of data warehouse architecture and retail data sources
• Experience with BI tools such as Power BI or Tableau
• Proficiency in statistical experimentation and A/B testing
• B.Tech / B.Sc in Statistics, Mathematics, Computer Science, or a related field

Preferred Qualifications

• MBA in Analytics or Business
• Experience with Azure Databricks or BigQuery
• Knowledge of GTM, event tagging, and pixel setup
• Exposure to recommendation engines or personalization analytics
• Experience with Python/R for statistical modelling or machine learning
• Familiarity with Jira