• Played a pivotal role in developing the Generative Market Analysis (GMA) product which is part of Accenture’s Gen AI capabiilty, enabling Oracle Cloud Infrastructure with real-time market research updates, executive strategy briefings, and on-demand strategic insights. • Spearheaded the front-end development of a high-performance, responsive UI for the GMA tool using React.js and TypeScript, that helped leadership enhance proposal initiation and project execution by providing tailored growth strategies through detailed data analysis to address specific client needs. • Optimized application performance through the strategic implementation of lazy loading, code splitting, custom react hooks, resulting in a substantial 30% improvement in initial load time, ensuring a seamless user experience and enhancing user engagement. • Integrated Nivo network graphs based on D3.js for enhanced data-driven insights on industry trends and sources, which help reduced decision making time for leadership by 20%. • Developed reusable UI components adhering to WCAG 2 Level AA accessibility standards and BEM methodology using semantic HTML, CSS, JavaScript contributing to a more inclusive product and reducing code maintenance time. • Developed a component tracing feature in the Fabricator UI toolkit, enabling identification of 300+ components across 100+ pages, reducing search time by 25% and streamlining team workflows. • Collaborated with backend team to implement a real-time data communication system using WebSocket and React Chatbot Kit library, integrating Accenture CORE DB and OpenAI API. This solution ensured seamless, bidirectional communication while mitigating CSRF vulnerabilities and safeguarding data protection.

- Built Models based on Linear Regression, KNN Algorithm, Decision Tree Algorithm, Random Forest Regression.- Created Supervised Machine Learning Model which predicted Chance of Admit in university with 88.3% accuracy.