About Me
Detail-oriented Data Science enthusiast with internship experience at Gradtwin and hands-on projects in machinelearning, deep learning, and predictive analytics. Skilled in Python, SQL, Streamlit, and Power BI, with a pr…
Detail-oriented Data Science enthusiast with internship experience at Gradtwin and hands-on projects in machinelearning, deep learning, and predictive analytics. Skilled in Python, SQL, Streamlit, and Power BI, with a proven ability tobuild and deploy interactive ML apps. Brings prior operational experience in warehouse management, combining technicalexpertise with organizational skills to deliver accurate, efficient solutions.
Experience
Data Science Intern
Applied machine learning and deep learning techniques using Python to build predictive models. Developed interactive dashboards and apps with Streamlit and Power BI. Leveraged SQL for data extraction and preprocessing, ensuring clean datasets. Collaborated on end-to-end workflows, coding and debugging in Visual Studio Code (VS Code).
Junior 3d Artist
Created high-quality 3D models, textures, and visual assets based on project requirements. Designed & developed 3D environments, objects, and animations using industry-standard software. Collaborated with designers and developers to ensure visual consistency and accuracy in projects.
Assistant Manager - Medical Warehouse
Maintained accurate inventory records by entering incoming medicines into the company system, ensuring billing staff had real-time visibility of stock availability. Streamlined order fulfillment by coordinating with collection staff, updating bills to reflect stock changes, and supporting last-minute adjustments requested by sales personnel. Provided leadership support by overseeing warehouse operations in the manager’s absence, ensuring smooth workflow and adherence to procedures.
PROJECTS
Followers prediction
Social media growth is a key indicator of influence and reach. This project leverages historical engagement data (likes, comments, shares, views, posting frequency, etc.) to forecast follower growth. By applying machine learning techniques, the model identifies patterns that drive audience expansion and provides actionable insights for optimizing content strategies.