Entry-level Machine Learning Engineer and Data Scientist skilled in Python, Scikit-learn, XGBoost, TensorFlow, Pandas, FastAPI, Streamlit, Docker, Natural Language Processing (NLP), and SQL. Delivered models with 90%+ accuracy on real-world datasets and deployed production-ready apps via Streamlit, Docker, and REST APIs. Oracle-certified Data Scientist and Microsoft Azure AI certified.

ML / AI: Classification, Regression, Feature Engineering, Hyperparameter Tuning, Cross-Validation, SMOTE, Model Evaluation, EDA, NLP, Deep Learning, Predictive Modeling, Imbalanced Learning, Statistical Modeling, Model Deployment

Pickle, Joblib, docker-compose, Render, CI/CD Fundamentals, Jupyter Notebook

Power BI (DAX, Star Schema, Power Query), Geopy, Automated EDA

Technologies: Python, XGBoost, Scikit-learn, SMOTE, Streamlit, Geopy, Plotly, Pandas, Joblib, Python-dotenv

• Real-time risk prediction using XGBoost on geospatial features (rainfall, slope, elevation, soil type) + SMOTE for class imbalance
• Geolocation pipeline via Geopy, secure config with python-dotenv, model serialization with Joblib
• Live deployment: Streamlit web app with real-time Plotly dashboards and dynamic input forms
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Technologies: Python, Scikit-learn, SMOTE, FastAPI, Docker, Streamlit, Pandas, GridSearchCV, Render

• 93% accuracy (Precision: 0.92, Recall: 0.91, F1: 0.92) on 10,000+ insurance records via GridSearchCV + 5-fold CV
• +18% minority recall with SMOTE; 15+ predictive features engineered via IQR outlier removal
• Deployed: Pickle-serialized model on FastAPI, containerized with Docker + docker-compose, hosted on Render
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Technologies: Python, Scikit-learn, Pandas, Matplotlib, Seaborn, Power BI, Pickle

• 88%+ accuracy across 3 benchmarked models (Logistic Regression, Random Forest, Decision Tree) with k-fold CV + ROC-AUC
• Top 8 churn drivers identified via feature selection and RFE
• Deployment: Power BI dashboard with DAX measures; Pickle-packaged model for real-time REST API scoring
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Python Programming Intern · DATASOFTX (Startup), Chennai · Jan – Feb 2025

• Built a data-driven Student Management System using Python and Pandas with OOP principles
• Improved data accuracy by 60% via structured exception handling and input validation
• Managed codebase with Git & GitHub following CI/CD and SDLC best practices

Bachelor of Engineering in Computer Science and Engineering

• Saveetha School of Engineering, Chennai
• CGPA: 8.21/10
• Graduation: May 2025

Class XII – Intermediate (MPC)

• Sri Chaitanya Junior College, Vijayawada — 80.3% (Mar 2021)

Class X – SSC

• Flora English Medium School, Vuyyuru — GPA: 9.7/10 (Apr 2019)

• Oracle – Data Science Professional (2025)
• Cisco – Data Analytics Essentials (2025)
• Microsoft – Azure AI Fundamentals: Generative AI (2024)
• Udemy – Python Programming (2024)

✨ Open to collaborations, freelance projects, and internship opportunities!