Varsha Reddy Chintala

Software Engineer with 3+ years of experience in developing data-driven solutions using Microsoft Power Platform, Power BI, SQL, and Azure technologies. Experienced in building scalable data pipelines, automating reporting systems, and improving business intelligence processes. Currently pursuing a Master’s in Computer Science at the University of North Texas with a strong interest in data engineering, analytics, and cloud-based solutions.

• Programming for Everybody (getting started with python) - Coursera
• Artificial Intelligence Course - Coursera
• Querying Data with Transact-SQL Introductory Course - Microsoft
• Analyzing and Visualizing Data with Microsoft Power BI - Microsoft
• Implementing an Azure Data Solution - Microsoft
• Developing SQL Databases - Microsoft
• Microsoft Fabric - DP600 - Microsoft

Context-Aware Travel Itinerary Generator

• Developed an NLP-based recommendation system that converts natural language travel descriptions into personalized day-by-day itineraries.
• Implemented context extraction using spaCy/NLTK to identify trip details such as location, duration, and traveler preferences.
• Integrated Google Places, Yelp, and Wikivoyage APIs to retrieve attraction data and applied filtering and ranking algorithms to generate relevant recommendations.
• Built a simple web interface using Flask/FastAPI and React/Streamlit for generating customized travel plans.

CuisineConnect – Restaurant Management Portal | MongoDB, Express.js, React.js, Node.js (MERN Stack)

• Developed a full-stack restaurant management web application enabling users to browse menus, reserve tables, and place dine-in, takeaway, or delivery orders.
• Designed features such as table reservation, real-time order tracking, and menu customization to enhance customer experience.
• Built an admin dashboard for restaurant owners to manage tables, orders, and customer interactions.
• Implemented JWT-based authentication and scalable backend APIs to support multi-user activity.

Index Price Prediction using Machine Learning | Python, Deep Learning

• Built a stock index prediction model using deep learning architectures including MLP, LSTM, CNN, and Attention-based models.
• Analyzed historical financial data to forecast trends for S&P 500, CSI 300, and Nikkei 225 indices.
• Evaluated model performance across multiple markets to improve prediction accuracy.

QUELIFE Animal Shelter Database System | Oracle SQL, Database Design

• Designed a relational database system to manage animal shelter operations including facilities, animals, employees, volunteers, adoptions, and veterinary records.
• Developed complex SQL queries for data analysis, including tracking employee work hours, identifying animals staying in shelters for more than 30 days, and analyzing shelter capacities.
• Implemented data manipulation operations (INSERT, UPDATE, DELETE) to maintain records such as volunteer availability, adopter information, and animal status.
• Created queries to generate reports such as payroll calculations, adoption tracking, and shelter facility analysis.