shubhambhatia0321@gmail.com ⋄ linkedin.com ⋄ Github.com
B.Tech, IT | Inderprastha Engineering College (2020-2024) XII, CBSE | SSD Saraswati Bal mandir (2020) X, CBSE | SSD Saraswati Bal mandir (2018)
Languages: Python Programming, C++, MySQL.
Developers Tools: VS Code, Git, Google Colab, Jupyter Notebook.
Technologies/Framework: Machine learning libraries, AWS (Lambda, Lex, S3), QuickSight, ETL, Data Warehousing, BeautifulSoup4, Docker, Streamlit
Cognizant Artificial Intelligence Job Simulation on Forage
- Conducted exploratory data analysis (EDA) for Gala Groceries using Python and Google Colab.
- Developed Python module for training machine learning models and outputting performance metrics.
- Utilized skills: Data Analysis, Data Modeling, Data Visualization, Machine Learning, Python.
J.P. Morgan Software Engineering Virtual Experience on Forage
- Set up a local dev environment by downloading the necessary files, tools, and dependencies.
- Utilized JPMorgan Chase’s open-source library Perspective to generate a live graph that displays a data feed in a clear and visually appealing way for traders to monitor
- Utilized skills: Basic Programming, Contributing to The Open-Source Community, Financial Analysis, Web Applications, Python, Technical Communication, Git, Typescript.
Twitter Sentiment Analysis Developed a deep learning model that trains on 1.6 million tweets for sentiment analysis to classify any new tweet as either being positive or negative. (Try it here)
- Achieved 78.2% accuracy in sentiment analysis using NLP techniques.
- Led implementation of NLP algorithms, improving sentiment analysis accuracy.
- Optimized model performance with data preprocessing, stemming, feature extraction.
- Utilized Kaggle API, manipulated Sentiment140 dataset for analysis.
Conversational-Chatbot-Groq Developed Groq API Chat Assistant to enhance Customer Support and Information Retrieval by using Large Language Models (LLMs) and NLP. (Try it here)
- Utilized LangChain API to build Streamlit applications that enhance user engagement and accessibility.
- Integrated the Groq API seamlessly for contextually relevant responses through NLP.
- Managed session state to autonomously save and display chat history to enhance user interaction.
- Improved user satisfaction and experience by implementing a robust conversational interface.
Credit Scoring Model Developed Logistic Regression model for credit scoring, enabling data-driven lending strategies for banks. (Try it here)
- Achieved 83% accuracy in developing a machine learning model using Logistic Regression to predict loan default risk.
- Led implementation of decile methodology to optimize lending strategies, improving profitability and market reach.
- Utilized Python and libraries for data processing, model training, and evaluation.
- Integrated reusable project structure for scalability and knowledge transfer, enhancing code maintainability.
- Problem-Solving by CodeChef: Ready to apply Python enriched skill set to real-world challenges.
- Mode SQL: Exploration of all the fundamental topics such as data manipulation, querying, and database management.
Data Structures & Algorithms - OOPS - Operating System - DBMS - Computer Networks - DAA - ML
- 5-star Gold Badge in SQL on HackerRank.
- 4-star Silver Badge in 30 days of code on HackerRank.
- 3-star Silver Badge in C++ on HackerRank.
- Earned Microsoft Azure AI Fundamentals: Generative AI Trophy.