Ujwala Velpula
Professional Summary
Data Analyst with 0 years of experience specializing in data analytics and full-stack development. Proficient in SQL, Python (Pandas, NumPy), Excel, Power BI, and Tableau for data cleaning, EDA, statistical analysis, and dashboarding. Hands-on experience building end-to-end web applications (React, Node, MongoDB) enabling close collaboration with engineering teams on data pipelines and reporting. Seeking a Data Analyst role to apply data storytelling and analytical problem-solving to support business decisions.
Technical Skills
Work Experience
- Designed and implemented RESTful APIs for user authentication and CRUD operations using Node.js and Express to support front-end product features and user flows.
- Built responsive React.js interfaces integrated with backend APIs, improving UI consistency and reducing frontend integration issues during testing.
- Designed MongoDB schemas and implemented query optimizations to improve data retrieval efficiency for user and session data.
- Implemented server-side input validation, error handling, and logging to improve backend reliability and simplify debugging across services.
- Collaborated with peers using Git and GitHub for source control and pull-request driven development to deliver features within sprint cycles.
- Supported cloud deployment tasks and troubleshooting, using AWS tooling and local debugging to reduce deployment-related defects.
- Integrated React frontend with a MongoDB-backed Node.js API to enable real-time data management for platform features and user interactions.
- Implemented API integration and client-side state handling to improve responsiveness and reduce synchronization issues between UI and backend.
- Used GitHub for version control and participated in code reviews to maintain code quality and accelerate delivery.
- Developed responsive UI components using HTML, CSS and React to improve usability across devices.
- Optimized server-side queries and assisted in schema updates to support new platform features and data models.
- Documented development processes and troubleshooting notes to streamline handoffs and onboarding for subsequent contributors.
- Developed dynamic web pages using HTML, CSS, and JavaScript to support interactive learning modules and frontend features.
- Implemented frontend-backend integration patterns and basic backend routes to connect UI with data sources and application logic.
- Worked on database connectivity and basic schema design to store and retrieve application content reliably.
- Deployed sample applications and practiced cloud deployment workflows to understand CI/CD and hosting concepts.
- Followed software engineering practices, participated in team problem-solving, and delivered project milestones within the internship timeline.
- Improved debugging skills and collaborated with mentors to refine code quality and application structure.
Projects
- Cleaned and transformed raw CSV transaction datasets using Excel functions and data validation to prepare for analysis.
- Performed exploratory data analysis to identify trends, seasonality, and outliers affecting transaction volumes and values.
- Built interactive dashboards in Power BI and Tableau to present key financial metrics, trends, and performance indicators.
- Created PivotTables and PivotCharts to summarize transaction segments and support stakeholder decision-making.
- Generated actionable business insights and visualizations to highlight revenue drivers and areas for operational focus.
- Developed an AI-powered mental health chatbot using Python and Streamlit to provide a conversational user interface.
- Integrated pretrained transformer models from Hugging Face and fine-tuned pipelines in PyTorch for intent and sentiment detection.
- Implemented NLP preprocessing and sentiment analysis to identify user emotions and guide supportive responses.
- Deployed the application on Streamlit Community Cloud to enable web access and real-time interactions.
- Worked on model integration, inference optimization, and user-facing prompts to improve conversation relevance and responsiveness.
- Built a traffic detection system using OpenCV to detect and analyze vehicles in images and video streams.
- Implemented frame processing and object detection techniques to identify moving vehicles and count occurrences.
- Applied image processing filters and contour analysis to improve detection accuracy under varying lighting conditions.
- Optimized frame analysis to reduce processing time and enable near-real-time detection for test datasets.
- Documented algorithm design and testing methodology to support reproducibility and further enhancements.
Education
Certifications
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