Indore, Madhya Pradesh, India
Performed end-to-end Sales Data Analysis and Forecasting using the Global Superstore dataset to identify revenue trends, customer behavior, and product performance. • Cleaned and transformed large retail datasets using Python (Pandas, NumPy) to handle missing values, duplicates, and data inconsistencies. • Conducted detailed Exploratory Data Analysis (EDA) to analyze regional sales, product categories, discount impact, and seasonal demand patterns. • Built interactive visualizations using Matplotlib, Seaborn, and Plotly to uncover business insights and performance trends. • Implemented RFM Customer Segmentation to identify high-value customers and support targeted marketing strategies. • Developed time-series forecasting models (ARIMA & Facebook Prophet) to predict future sales and demand fluctuations. • Evaluated model performance using metrics such as RMSE and MAPE to ensure forecasting accuracy. • Designed interactive business dashboards using Power BI/Tableau for stakeholder decision-making. • Generated actionable recommendations to improve inventory planning, discount strategies, and regional sales performance. • Delivered a complete analytics solution including cleaned datasets, forecasting outputs, dashboards, and executive business reports.