Sneha Edupuganti
Software Developer | Data Analyst | Machine Learning Engineer
Transforming data into actionable insights and building intelligent solutions.
About Me
I am a Computer Science graduate student at the University of Florida with a strong foundation in data analysis, backend engineering, and machine learning. My journey began during my undergraduate studies at VIT-AP University, where I developed a passion for transforming data into actionable insights and building scalable software solutions.
Currently pursuing my Master's degree, I am focused on advancing my expertise in artificial intelligence, natural language processing, and distributed systems. My professional experience spans finance automation, backend development, and data analytics across various industries including healthcare, IoT, and pharmaceuticals.
I am passionate about leveraging technology to solve real-world problems and am constantly exploring new methodologies in machine learning and data science. I enjoy working on full-stack projects and have experience building end-to-end solutions from data processing pipelines to interactive dashboards.
Education
Grade: 3.9/4.0
Key coursework: Advanced Data Structures, Distributed Operating Systems, Analysis of Algorithms, Artificial Intelligence, Programming Languages, Natural Language Processing, Data Science, Project Management, Multimedia Systems
Grade: 3.9/4.0
Key coursework: Java Programming, C Programming, Data Analytics, Machine Learning, Database Management, Computer Networks, Object-Oriented Programming, Computer Architecture, Web Technologies, Software Engineering, Mobile Application Development, NoSQL Databases, Cloud Computing
Skills
Programming Languages
Frameworks/Tools
Cloud/Infrastructure
Data/ML
Projects
Built a full-stack sentiment analysis dashboard for retail customer reviews to support product strategy decisions
Compared BERT, LSTM, and Logistic Regression models; deployed the best-performing one using Flask and Plotly Dash with real-time sentiment and keyword insights
Created a web-based diagnostic platform using XGBoost and Scikit-learn to support early-stage kidney disease identification, with Flask APIs and PostgreSQL integration
Performed data cleaning, feature engineering, and statistical validation, improving model reliability and interpretability for clinical insights
Built a full-stack issue tracking platform using MongoDB, Express, React, and Node.js, enabling seamless collaboration across development and DevOps teams
Implemented real-time updates via WebSockets, role-based permissions, and audit trails, enhancing operational visibility and team accountability
Developed a Pascal compiler using LLVM framework for code generation and optimization. Implemented lexical analysis, parsing, and intermediate code generation.
Built a deep learning model for pneumonia detection from chest X-ray images using convolutional neural networks. Achieved high accuracy in medical image classification.
A comprehensive ticket management system designed for event ticketing and reservation management. Built to handle ticket sales, seat allocation, and event management with a user-friendly interface.
Features include real-time seat availability, secure payment processing, and administrative dashboard for event organizers to manage bookings and track sales analytics.
Experience
- Automated reporting using Python and Excel macros, reducing manual effort by 40% and improving data accuracy; built Power BI dashboards for real-time KPI tracking
- Audited SQL models with Pandas and Excel to ensure data quality and support confident decision-making across departments
- Built RESTful APIs with Flask and PostgreSQL to process high-volume IoT telemetry data, improving efficiency by 30%; integrated Kafka and Docker for reliable, asynchronous workflows
- Deployed microservices with RBAC and cloud integration, enhancing security, modularity, and CI/CD across environments
- Automated ETL workflows using SQL, Flask, and cron jobs to streamline data processing for over 50,000 records/month across multiple business verticals, reducing manual workload and improving data accuracy and pipeline efficiency
- Developed interactive Tableau dashboards to uncover real-time trends, enabling stakeholders across compliance, operations, and strategy teams to make data-driven decisions
- Conducted market research and customer interviews to revamp the go-to-market strategy for an underperforming unit; created a standardized analysis manual, boosting execution speed by 166%
- Analyzed 16 business opportunities, validated models for two ventures, and built Excel dashboards to visualize profitability trends from social media for strategic content planning
Certifications & Achievements
Extra-curriculars
Supporting event operations and guest services at the university's premier sports and entertainment venue.
Managing recreational facilities and providing assistance to students in campus game room activities.
Assisting students with textbook purchases, merchandise, and general bookstore operations.
Managed chapter communications, organized technical events, and maintained member records for the CSI student chapter.
Managed club finances, budgeting for technical competitions, and coordinated funding for student participation in hackathons.
Served as the elected Program Representative for a cohort of 1,200+ undergraduate students, acting as the primary liaison between students and faculty administration.
Get In Touch
Feel free to reach out for collaborations, opportunities, or just to say hello!