Data Scientist at HostyNest

Developed AI-driven personalized homestay recommendation pipelines using Python and TensorFlow, achieving a 15% uplift. Built AI-powered chatbot with Azure Bot Services and NLP for real-time student/host assistance. Implemented AI-based document verification for compliance onboarding. Led full-stack development of React/TypeScript front-end and ASP.NET Core RESTful API back-end, establishing CI/CD pipelines using GitHub Actions.

Software Engineer at Veersa Technologies India

Led full-stack backend and frontend development using C#, ASP.NET, Visual Basic, Angular, PostgreSQL, and NoSQL to enhance system efficiency and scalability. Supervised and implemented new client product functionalities across multiple teams and environments. Acted as team leader during critical technical escalations ensuring smooth project execution. Designed and developed MVP using React TypeScript, Python3, and Generative AI within three weeks. Integrated AWS Polly for text-to-speech in US-based e-learning portals. Collaborated cross-functionally with JIRA and Git to deliver product optimizations.

Data Science Intern at Veersa Technologies India

Worked on Azure Data Factory, Databricks, and Synapse to develop and optimize data pipelines. Designed and implemented a hybrid machine learning and deep learning model for disease prediction deployed in US hospitals. Developed handwritten document processing solutions using AWS Textract and other AWS services with Python3, Flask, and VueJs. Integrated AWS and Azure AI services to improve automation and scalability in healthcare solutions.

Software Development Engineer Intern at EdenEco Smart Homes

Designed and implemented an LSTM-based deep learning model to predict hourly electricity consumption for the AEP Power Grid. Applied advanced deep learning techniques for time series forecasting to improve energy consumption accuracy.

Data Scientist at HostyNest

AI-Driven Recommendations: Developed predictive modeling pipelines in Python and TensorFlow, achieving 15% uplift in personalized homestay recommendations. Chatbot Development: Built AI-powered chatbot using Azure Bot Services, and NLP techniques for real-time student/host assistance. Document Verification: Implement AI-based compliance checks for onboarding. Full-Stack Development: Led full-stack development of React/TypeScript front-end and RESTful API back-end (ASP.NET Core), with CI/CD pipelines in GitHub Actions.

Software Engineer at Veersa Technologies India

Full-Stack Development: Led backend and frontend development using C#, ASP.NET, Visual Basic, Angular, PostgreSQL, and NoSQL, enhancing system efficiency and scalability. Product Optimization: Supervised and implemented new functionalities to optimize client products, collaborating across three teams and six environments to improve performance. Crisis Management & Team Leadership: Stepped up as a team leader during high-pressure situations, addressing critical technical escalations. MVP Development & AI Integration: Designed and developed a Minimum Viable Product (MVP) using React TypeScript, Python3, and Generative AI within three weeks. Text-to-Speech Implementation: Integrated AWS Polly to enable text-to-speech capabilities in an e-learning portal, successfully deployed in US-based education platforms. Cross-Functional Collaboration: Collaborated cross-functionally using JIRA and Git, delivering client-facing product optimizations across three environments.

Data Science Intern at Veersa Technologies India

Azure Data Engineering: Worked with Azure Data Factory, Databricks, and Synapse to develop and optimize data pipelines for efficient data processing. Machine Learning & Deep Learning: Designed and implemented a hybrid ML-DL model for disease prediction, deployed in US hospitals to enhance diagnostic accuracy. AI-Powered Document Processing: Developed a handwritten document processing solution using AWS Textract, S3, ECR, Lambda, EC2, Python3, Flask, VueJs, and MSAL, enabling automated extraction and storage of medical and insurance forms. Cloud & AI Integration: Integrated AWS & Azure AI services to enhance automation, scalability, and performance in data-driven healthcare solutions.

Software Development Engineer Intern at EdenEco Smart Homes

Designed and implemented an LSTM-based deep learning model to predict hourly electricity consumption for the AEP Power Grid. Time series forecasting: Applied advanced deep learning techniques to analyze energy consumption patterns and improve forecasting accuracy.

Data Scientist at HostyNest

Led AI-driven recommendations using Python and TensorFlow, achieving a 15% uplift in personalized homestay recommendations. Built an AI-powered chatbot with Azure Bot Services for real-time student/host assistance. Implemented AI-based document verification for onboarding compliance. Managed full-stack development of a React/TypeScript front-end and RESTful ASP.NET Core back-end, with GitHub Actions CI/CD pipelines.

Software Engineer at Veersa Technologies India

Led backend and frontend development using C#, ASP.NET, Visual Basic, Angular, PostgreSQL, and NoSQL to enhance system efficiency and scalability. Supervised feature delivery to optimize client products across three teams and six environments. Served as team lead during high-pressure escalations. Designed MVPs using React TypeScript, Python, and Generative AI within three weeks. Integrated AWS Polly for text-to-speech in an e-learning portal deployed in US education platforms. Collaborated cross-functionally using JIRA and Git to deliver client-facing optimizations across three environments.

Data Science Intern at Veersa Technologies India

Azure Data Engineering: developed and optimized data pipelines using Azure Data Factory, Databricks, and Synapse. ML/DL model for disease prediction deployed in US hospitals to improve diagnostic accuracy. AI-powered document processing: developed handwritten document processing using AWS Textract, S3, ECR, Lambda, EC2, Python, Flask, Vue.js, and MSAL for automated extraction and storage. Cloud & AI integration: combined AWS & Azure AI services to boost automation, scalability, and performance in data-driven healthcare solutions.

Software Development Engineer Intern at EdenEco Smart Homes

Developed an LSTM-based deep learning model to predict hourly electricity consumption for the AEP Power Grid. Applied time-series forecasting techniques to analyze energy consumption patterns and improve forecasting accuracy.

Data Scientist at HostyNest

AI-Driven Recommendations: Developed predictive modeling pipelines in Python and TensorFlow, achieving a 15% uplift in personalized homestay recommendations. Chatbot Development: Built AI-powered chatbot using Azure Bot Services and NLP for real-time student/host assistance. Document Verification: Implement AI-based compliance checks for onboarding. Full-Stack Development: Led full-stack development of React/TypeScript frontend and RESTful API backend (ASP.NET Core), with CI/CD pipelines via GitHub Actions.

Software Engineer at Veersa Technologies India

Quarto & Python Integration: Installed and managed Quarto and Python versions for reproducible workflows and publishing. Full-Stack Development: Led backend and frontend development using C#, ASP.NET, Visual Basic, Angular, PostgreSQL, and NoSQL, enhancing system efficiency and scalability. Posit Workbench & Package Manager: Installed and configured Posit Workbench on Ubuntu servers with R and Python environments; assisted in configuring Posit Connect for publishing ML models and reports, and set up CRAN/Bioconductor repositories with Posit Package Manager for controlled package distribution. System & Network Setup: Verified server prerequisites (OS, CPU, RAM, disk space) and configured secure network access for repositories and license validation. MVP Development & AI Integration: Designed and developed a Minimum Viable Product (MVP) using React TypeScript, Python3, and Generative AI within three weeks to meet client requirements. Text-to-Speech Implementation: Integrated AWS Polly to

Data Science Intern at Veersa Technologies India

Azure Data Engineering: Worked with Azure Data Factory, Databricks, and Synapse to develop and optimize data pipelines for efficient data processing. Machine Learning & Deep Learning: Designed and implemented a hybrid ML-DL model for disease prediction, deployed in US hospitals to enhance diagnostic accuracy. AI-Powered Document Processing: Developed a handwritten document processing solution using AWS Textract, S3, ECR, Lambda, EC2, Python3, Flask, VueJs, and MSAL, enabling automated extraction and storage of medical and insurance forms.