• Developed personalized shopping features using content-based and collaborative filtering algorithms, improving conversion rate by 65%• Architected and maintained an Elasticsearch search engine by leveraging RESTful APIs to streamline data indexing processes. Implemented Kibana dashboards for real-time monitoring and data visualization, achieving a 51% reduction in search response times and enhancing query efficiency• Designed and implemented a data-calling feature integrated with web service APIs to facilitate device and agent communication, resulting in a 23% increase in mobile traffic and contributing to record sales in 2023• Built and optimized RESTful APIs in Node.js for B2B order management, invoicing, and communication processes, serving over 5,000 clients per month, resulting in a 30% increase in data processing speed and a 25% reduction in API response time• Improved runtime performance by creating a module to handle B2B logic for SSR, replacing deprecated logic in a single API request, reducing server load by 25%, raising pagespeed 3x, resulting in enhanced user experience

• Designed and developed multiple enterprise-level micro-service applications for the Home team, increased the annual revenue by 64% using the latest technologies Vue.js, JavaScript, SASS, FTL, and XML.• Implemented new components to an existing web application with a Mobile-First code that reaches 150M+ users each month. Resulting in an increase in mobile traffic by 11%.• Refactored existing features into Vanilla JS and redesigned the UI, and code refactoring, reduced errors, and improved performance across the entire code base.• Managed the Continuous Integration/Deployment pipeline(Jenkins), conducted Code Reviews, Integration, E2E Testing.

• Designed and implemented enterprise applications for Thales Group’s Railway Platforms allowing engineers to perform data analysis and experiments using technologies including Flask, React, Azure, and MySQL in Thales Signaling Division.• Built the core features of Thales Network System, resulting in the ability to generate network optimization, manipulate data, and detect network errors automatically.• Automated DLS configuration report by creating an automated daily email to the stakeholders, providing a visual analysis of the company’s railway system, improving the speed and accuracy of reporting.

• Conducted Data Mining of a large dataset extracted from mobile App Development Teams ensuring 100% level of accuracy.• Planned and coordinated NLP Topic Modelling by proposing LDA algorithms and Gibbs Sampling Option that ended up in the IEEE digital library.• The paper got accepted and is published in the IEEE digital library.