Data Analyst – Retail Analytics

2 days ago

Bangalore Division, India EPISEIO Business Solution Full time

Role Overview As a Lead Data Scientist / Data Analyst, you’ll combine analytical thinking, business acumen, and technical expertise to design and deliver impactful data-driven solutions. You’ll lead analytical problem-solving for retail clients — from data exploration and visualisation to predictive modelling 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 optimisation). • 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 You’ll Work On • Customer segmentation (RFM, mission-based, behavioural) • Price and promo effectiveness • Assortment and space optimisation • 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 visualisation 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 Fill in the form, we will contact you...

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