👨‍💻 Professional Summary

Master's Student in Data Science with 1 year of research and practical experience in Data Science and Machine Learning. Demonstrated proficiency in Python, Java, SQL, statistical modeling, and Keras (LSTM/RNN), Scikit-learn, Data Visualization, etc. Strong history of projects and research contributions, including an LLM chatbot and predictive modeling applications, displaying advanced problem-solving abilities and technical expertise. Driven to use innovative machine learning and data science techniques to solve challenging problems in the Artificial Intelligence industry and apply academic research to create effective, data-informed solutions.

Data Science & Machine Learning: Gen AI • Statistical Analysis • Predictive Modeling • Big Data Analytics • NLP
Programming & Tools: Python • SQL • C • Java • AWS • AWS Hadoop • Full Stack • API • S3 • RAG
Research & Analysis: Data Science Pipelines • Experimental Design • Academic Research

🎓 Education

Master of Science in Data ScienceCurrent
Aug 2025 - Expected 2027
Tagliatela College of Engineering, University of New Haven • West Haven, CT

Coursework:

Data Science Machine Learning Big Data Data Visualization Data Engineering Introduction to AI

Tools & Technologies:

Python SQL TensorFlow Scikit-learn PyTorch Hadoop Tableau AWS Spark Matplotlib Plotly Seaborn Flask Streamlit

Models Used:

Random Forest XGBoost Logistic Regression KNN Clustering Dimensionality Reduction Linear Regression
Bachelor of Technology in Computer Science and Engineering
Apr 2020 - Aug 2024
Institute of Technical Education and Research, Siksha 'O' Anusandhan University • IndiaCGPA 7.5

Core Engineering Coursework:

Java Programming C Programming OOP Data Structures & Algorithms Digital Logic Design Computer Networks Operating Systems DBMS Software Engineering

💼 Professional Experience

Machine Learning Intern
Jan 2025 - Apr 2025
Unified Mentor (Remote)
  • Contributed to projects including Fraud Detection, Lung Cancer Prediction, Vehicle Price Prediction, and Animal Classification, applying data science techniques to solve real-world problems in healthcare, finance, and automotive domains.
  • Designed and implemented ML models and algorithms with data preprocessing, feature engineering, and hyperparameter tuning, improving prediction accuracy and model efficiency across projects.
  • Collaborated with cross-functional teams to analyze large datasets, delivering actionable insights and robust model evaluation metrics to ensure reliable outcomes.
  • Utilized Python, scikit-learn, and related libraries to develop predictive models and workflows for each project.
  • Presented results and visualizations to stakeholders, guiding data-driven decisions and demonstrating model impact on project objectives.

🚀 Data & AI Projects Portfolio

AWS S3 & Web Integration + AWS EC2 DeploymentUniversity Project
Aug 2025 - Present
University of New Haven • Master's Program
  • Utilized AWS S3 buckets for secure data storage and delivery, integrating with web interface to enable seamless data access and management.
  • Created and configured an EC2 instance on Ubuntu to host a dynamic web application, demonstrating proficiency in cloud deployment and server management.
Specification Comparator with Basic RAG
Jan 2026
  • Developed a Retrieval-Augmented Generation (RAG) system using OpenAI GPT models to extract and compare structured specifications from unstructured PDF documents.
  • Built an LLM-powered comparison pipeline with PDF parsing, semantic extraction, Streamlit visualization, and Excel export, ensuring robust handling of missing data.
Design Exam Query Chatbot
Dec 2024 - Jan 2025
  • Built a Generative AI-based chatbot using machine learning and NLP to answer design exam-related queries accurately.
  • Integrated SYL blog content to deliver context-aware responses, study strategies, and step-by-step exam preparation guidance.
  • Enhanced user engagement and preparation efficiency by providing personalized tips, ideas, and solution-focused insights.
COVID-19 Time Series Benchmarking
Dec 2024
  • Built comparative forecasting models (LSTM, RNN, ARIMA) for COVID-19 daily confirmed cases.
  • Performed stationarity testing (ADF), seasonal decomposition, and moving average smoothing.
  • Achieved superior performance using LSTM for nonlinear pandemic wave modeling.
  • Evaluated models using RMSE and R² metrics.
Fraud Detection using Machine Learning
2025
Unified Mentor Internship
  • Built an end-to-end credit card fraud detection system using Python, Scikit-learn, and SMOTE, engineering behavioral and time-based risk features from large-scale transaction data.
  • Improved fraud detection performance with Stratified Cross-Validation (ROC-AUC: 0.976) and performed model evaluation using confusion matrix, precision-recall curves, and feature importance analysis.
Animal Classification using Deep Learning
2025
Unified Mentor Internship
  • Developed a 15-class image classification system using a custom CNN and MobileNetV2 transfer learning, training on ~1,900+ images with data augmentation.
  • Achieved 73.8% validation accuracy using transfer learning, significantly outperforming the baseline CNN (6% accuracy).
  • Implemented early stopping, learning rate scheduling, confusion matrix analysis, and classification reports to optimize model performance; deployed inference pipeline and saved trained models for reuse.
Vehicle Price Prediction using ML
2025
Unified Mentor Internship
  • Developed a regression-based vehicle price prediction system using Random Forest and Ridge models, achieving R² = 0.79 on test data.
  • Built an end-to-end ML pipeline with data cleaning, feature engineering (vehicle age, log transformation), OneHotEncoding, and StandardScaler using scikit-learn Pipelines.
  • Implemented model evaluation (MSE, R², residual analysis) and deployed a reusable prediction function with model persistence using Pickle.
Stock Trading WebApp using Hybrid ModelFinal Year Project
Jan 2024 - Jun 2024
Lead in ML, Flask, and Blockchain • Undergrad Final Year Project
  • Developed a web application for stock trend prediction and automated trading using predictive analytics and machine learning.
  • Implemented blockchain-based security to ensure secure transactions and robust financial data protection.
  • Designed an intuitive, visually appealing UI to deliver a seamless user experience for secure economic management.
Vegetable Price Forecasting using Prophet
2024
  • Developed a time-series forecasting model using Facebook Prophet on 17+ years of market price data.
  • Performed data preprocessing, feature engineering, and seasonal trend analysis.
  • Forecasted future vegetable prices with confidence intervals for 365 days.
  • Visualized trend and seasonality components for market insight.

📚 Professional Certifications & Memberships

  • Machine Learning Engineer Learning Path
    Google Cloud / Google Skills
    2025 - Present
  • Complete Guide to SQL for Data Engineering: from Beginner to Advanced
    LinkedIn Learning / Deepak Goyal
    Feb 2026
  • SQL Tips and Tricks for Data Science
    LinkedIn Learning
    Feb 2026
  • Data Science Foundations: Data Engineering
    LinkedIn Learning
    Feb 2026
  • The Complete Python Bootcamp from Zero to Hero
    Udemy
    Jan 2025
  • JS and Full Stack Development
    Udemy
    Dec 2024
  • Java - The Complete Java Development Bootcamp
    Udemy
    Apr 2024
  • Machine Learning from Teachnook
    Teachnook
    Sep 2022

🛠️ Technical Skills

Python
SQL
Machine Learning
Data Science
Gen AI
NLP
Deep Learning
TensorFlow
PyTorch
Scikit-learn
Keras (LSTM/RNN)
AWS
AWS S3
AWS EC2
Hadoop
Big Data
Flask
Streamlit
RAG
LangChain
Tableau
Data Visualization
Statistical Modeling
Predictive Analytics
Java
C Programming