About Me
Computer Science and Engineering (Data Science) graduate with hands-on experience in Machine Learning, Natural Language Processing, Deep Learning, and Data Analytics through internships and end-to-end AI projects. Skilled in Python, SQL, Scikit-learn, TensorFlow, Power BI, and transformer-based NLP systems with experience in predictive modeling, feature engineering, and analytics.
Skills & Technologies
Work Experience
Data Science Intern
Engineered a Carrier Performance and SLA Risk Intelligence system using 100K+ logistics records. Performed EDA, feature engineering, and predictive modeling with Random Forest and Naive Bayes to build risk-classification workflows for SLA breach prediction and shipment delay detection. Developed Power BI dashboards and KPI reports to support operational decision making.
Machine Learning Intern
Developed ML and NLP models using Decision Trees, Logistic Regression, and TF-IDF for classification tasks. Conducted data preprocessing, feature engineering, and exploratory analysis on varied datasets. Built CNN-based image classification models using TensorFlow/Keras and designed collaborative filtering recommendation systems for personalized suggestions.
Projects
AI-Based Legal Contract Risk Analyzer
Developed an AI-powered legal contract intelligence platform for clause classification and risk assessment. Implemented TF-IDF, Logistic Regression, and LegalBERT models for automated contract analysis. Automated extraction of contractual clauses and legal risk indicators using NLP pipelines.
Carrier Performance & SLA Risk Intelligence
Developed a machine learning solution for shipment delay and SLA breach prediction. Built a user-friendly frontend and deployed the ML application on Railway for real-time predictions. Trained and evaluated Random Forest and Naive Bayes models for risk classification.
Employee Attrition Prediction System
Developed a machine learning model to predict employee attrition using workforce and behavioral datasets. Performed feature analysis to identify key factors influencing employee turnover and retention. Evaluated classification models and generated workforce-planning insights.
Education
B.Tech
Computer Science and Engineering (Data Science)