1- Collect, clean, and preprocess operational data from various sources, including point-of-sale systems, inventory databases, and customer feedback.2- Analyze data to identify trends, patterns, and anomalies related to sales, inventory levels, customer behavior, and operational processes.Collaborate with stakeholders to define key performance indicators (KPIs) and develop dashboards, reports, and visualizations that provide actionable insights.Monitor inventory turnover rates, stock levels, and product demand to optimize inventory management and reduce wastage.3- Evaluate store performance metrics, such as foot traffic, conversion rates, and average transaction value, to identify opportunities for operational improvements.Analyze customer buying patterns and segmentation to tailor marketing strategies, promotions, and product placements.4- Contribute to pricing strategies by assessing price elasticity and competitive positioning of products.Identify operational bottlenecks and inefficiencies, proposing data-backed solutions to streamline processes and enhance overall productivity.5- Provide actionable insights to support decision-making at both strategic and tactical levels.Stay updated on industry trends, emerging technologies, and best practices in data analysis and retail operations.

1 - Developed a machine learning model to categorize products depending on the name of the products using natural language processing and machine learning with accuracy 95 %.2 - Automating Data entry and Data quality workflow3- Data cleansing and Data migration to increase data accuracy4- Using sql queries to extract , transform and work on the dataset 5- Exploratory Data analysis using python for showing trends on the data monthly , quarterly , yearly6-Developed a machine learning to predict customer churn using Customers data available

using specialist tools to extract the data neededresponding to data-related queries and keeping track of theseanalysing data to identify trendssetting up processes and systems to make working with data more efficientresearching new ways to make use of dataproducing reports and charts communicating trends within data to non-specialistspresenting information generated from data to clients and managers