• Conducted lead source analysis to identify high-revenue channels, supporting strategic improvements in lead generation.• Analyzed customer orders, product performance, and monthly offer data to optimize sales strategies.• Communicated with payment vendors and banks to implement targeted credit card offers on specific products, boosting revenue and sales.• Created monthly review reports featuring key performance metrics and trends for executive review.• Utilized Python and libraries such as NumPy and Pandas for data cleaning, and Matplotlib and Seaborn for data visualization.• Extracted and processed data from GA4 and Looker Studio, delivering daily reports on platform performance and customer insights.

• Worked with a team at RNT Robotics to support educational services for Zhila Parishad government schools.• Collected data using web scraping and manual methods, converting unstructured or non-English data for analysis.• Conducted exploratory data analysis to uncover patterns and trends in school performance.• Analyzed school outcomes to guide resource allocation, prioritizing schools with positive training results.• Created dashboards for schools to visualize performance metrics and generated reports with key findings for stakeholders.• Gained skills in data extraction, cleaning, analysis, and reporting, contributing to the project’s success.

- Learn about how to deal with the large datasets like cleaning of data, processing , and analysis of data.- In this internship I learn how to deal with different types of file formats like JSON, EXCEL, CSV, PDF, DOC and also how to store data and extract data from these file using python.- Learn about different types of of visualization libraries in python like seaborn, matplotlib etc.