Data Scientist Retail teamCollaborating with a Consumer-Packaged Goods (CPG) team to design and implement machine learning driven solutions foranalyzing Panel Data and Point of Sale (POS) data to enhance business decision-making and market insights.• Developing Supervised ML algorithms like SVM, Random Forest, Decision tree etc to track and measure the KPIs like Profitability,Revenue generated, Market Share, Customer Lifetime Value (CLV), Basket Size etc and assured client with an easy model with bestperformance upto 95% which helped to know customer segmentation and churn analysis initiatives, while supporting the teamwith comprehensive final documentation and reporting.• Generating Cross validation and regularization methods to get improved F1 score and updated accuracies upto 90-95%.Data Scientist FP&A team• Provided ML based and visual based solutions to a Financial Planning & Analysis team.• Implemented Regression and classification models to understand about metrics like Pricing, market competitors, revenueetc.• Designed and implemented visualizations and dashboards using Power BI to enhance clarity on key performance indicators(KPIs) such as pricing and market trends, including real-time status updates.• Executed macros to streamline Excel data retrieval, reducing processing time by 75%.

Architected and implemented a variety of 10+ supervised and unsupervised machine learning models to address complexanalytical challenges and optimize performance rate on metrics like Profit Earned, Customer Retention, Location etc.• Employed linear regression analysis to identify the predictors influencing profitability and revenue by 20-25%.• Facilitating the pricing team to understand the customer behavior trends using K clustering and some python libraries likeMatplotlib and Seaborn which keeps a track on Panel data enhancements which in a whole saved a 20-30 % timeconsumption.• Built and deployed an Optical Character Recognition (OCR) solution utilizing libraries Keras and TensorFlow for the number platetext extraction achieving realtime data processing and storage of vehicle information, which improved gate throughput by 25%.

Created ML models, Dashboards and story-based solution to help a sales term to get a positive impact on their KPIslike Revenue, Customer Retention, Average Order Value (AOV) and to know which is their highest loyal subgroups.• Establishing sophisticated predictive models leveraging logistic and linear regression techniques to drive datainformed decision-making and for optimal solutions for problem-based scenarios.• Created dashboards through Tableau for understanding the one’s and competitor’s status which helped them to gain 50% morelearnings and increase in their Revenue generation.

Spearheaded the development and implementation of automation tool for a networking project utilizing Python scripts toautomatically access a client’s web-based data, integrating all credentials under the Lib Script Module.• Developed an automation system using Python with Selenium WebDriver, enabling execution of processes in milliseconds,contingent upon data strength.• Seamlessly integrated with existing workflows and empowering the team to manage increased client requests withoutrelying for additional resources

Helped team to create website using Bootstrap. Created several features, checkboxes and radio buttons. Wirked on both UI and back end.

Worked on a Django Web Development project where got an opportunity to be part of both front end and back end