As a Lead Data Scientist / Data Analyst, you will combine analytical thinking, business acumen, and technical expertise to design and deliver impactful data-driven solutions. Your role will involve leading analytical problem-solving for retail clients from data exploration and visualization to predictive modeling and actionable business insights. Key Responsibilities: - Partner with business stakeholders to understand problems and translate them into analytical solutions. - Lead end-to-end analytics projects from hypothesis framing and data wrangling to insight delivery and model implementation. - Drive exploratory data analysis (EDA), identify patterns/trends, and derive meaningful business stories from data. - Design and implement statistical and machine learning models (e.g., segmentation, propensity, CLTV, price/promo optimization). - Build and automate dashboards, KPI frameworks, and reports for ongoing business monitoring. - Collaborate with data engineering and product teams to deploy solutions in production environments. - Present complex analyses in a clear, business-oriented way, influencing decision-making across retail categories. - Promote an agile, experiment-driven approach to analytics delivery. Common Use Cases Youll Work On: - Customer segmentation (RFM, mission-based, behavioral) - Price and promo effectiveness - Assortment and space optimization - CLTV and churn prediction - Store performance analytics and benchmarking - Campaign measurement and targeting - Category in-depth reviews and presentation to the L1 leadership team Required Skills and Experience: - 3+ years of experience in data science, analytics, or consulting (preferably in the retail domain) - Proven ability to connect business questions to analytical solutions and communicate insights effectively - Strong SQL skills for data manipulation and querying large datasets - Advanced Python for statistical analysis, machine learning, and data processing - Intermediate PySpark / Databricks skills for working with big data - Comfortable with data visualization tools (Power BI, Tableau, or similar) - Knowledge of statistical techniques (Hypothesis testing, ANOVA, regression, A/B testing, etc.) - Familiarity with agile project management tools (JIRA, Trello, etc.) Good to Have: - Experience designing data pipelines or analytical workflows in cloud environments (Azure preferred) - Strong understanding of retail KPIs (sales, margin, penetration, conversion, ATV, UPT, etc.) - Prior exposure to Promotion or Pricing analytics - Dashboard development or reporting automation expertise (Note: Any additional details of the company were not provided in the job description.) As a Lead Data Scientist / Data Analyst, you will combine analytical thinking, business acumen, and technical expertise to design and deliver impactful data-driven solutions. Your role will involve leading analytical problem-solving for retail clients from data exploration and visualization to predictive modeling and actionable business insights. Key Responsibilities: - Partner with business stakeholders to understand problems and translate them into analytical solutions. - Lead end-to-end analytics projects from hypothesis framing and data wrangling to insight delivery and model implementation. - Drive exploratory data analysis (EDA), identify patterns/trends, and derive meaningful business stories from data. - Design and implement statistical and machine learning models (e.g., segmentation, propensity, CLTV, price/promo optimization). - Build and automate dashboards, KPI frameworks, and reports for ongoing business monitoring. - Collaborate with data engineering and product teams to deploy solutions in production environments. - Present complex analyses in a clear, business-oriented way, influencing decision-making across retail categories. - Promote an agile, experiment-driven approach to analytics delivery. Common Use Cases Youll Work On: - Customer segmentation (RFM, mission-based, behavioral) - Price and promo effectiveness - Assortment and space optimization - CLTV and churn prediction - Store performance analytics and benchmarking - Campaign measurement and targeting - Category in-depth reviews and presentation to the L1 leadership team Required Skills and Experience: - 3+ years of experience in data science, analytics, or consulting (preferably in the retail domain) - Proven ability to connect business questions to analytical solutions and communicate insights effectively - Strong SQL skills for data manipulation and querying large datasets - Advanced Python for statistical analysis, machine learning, and data processing - Intermediate PySpark / Databricks skills for working with big data - Comfortable with data visualization tools (Power BI, Tableau, or similar) - Knowledge of statistical techniques (Hypothesis testing, ANOVA, regression, A/B testing, etc.) - Familiarity with agile project management tools (JIRA, Trello, etc.) Good to Have: - Exp