Data Analyst
AI and Data Science graduate with hands-on experience in data analysis, SQL, Python, Power BI, data visualization, data cleaning, exploratory data analysis, dashboard development, and data-driven applications.
Echobrains
Jan 2026 – June 2026
Developed Python-based backend applications and data workflows using Flask, SQL, REST APIs, and modular software practices. Built data-processing workflows using Pandas and NumPy, with hands-on debugging, database management, and analytics reporting. Assisted with troubleshooting, testing, and software development lifecycle activities while collaborating on application and data-related tasks.
Bachelor of Engineering, Artificial Intelligence & Data Science
Graduated 2026
CGPA: 8.19
PUC
2020-2022
Percentage: 83%
Personal project. Designed and built a Python-based AI data platform for automated data cleaning, exploratory data analysis, insights, and machine learning recommendations; exposed functionality through backend services and an interactive UI. Implemented reusable data-processing workflows and deployed the application for live use.
Final year project. Designed a Python/TensorFlow Graph Neural Network pipeline to model drug-disease-target relationships and identify potential drug repurposing candidates. Built preprocessing, graph construction, and link-prediction workflows on biomedical datasets.
Built a computer vision pipeline in Python using OpenCV and YOLO to detect potholes and road surface damage from images and video. Handled data preparation, model inference, and result visualization.
Hackathon project. Built an NLP application using Python, TF-IDF, cosine similarity, embeddings and vector-search concepts, and an LLM-assisted workflow to match resumes with job descriptions and rank candidates.
Developed a Flask-based Python application that generates and debugs source code from natural-language prompts, emphasizing modular backend architecture, API integration, and debugging.