Open to opportunities

GAURAV KUMAR

@gauravkumar35

Message

Aspiring Machine Learning Engineer building end-to-end ML and deep learning applications with Python.

India

Message

What I'm looking for

I’m looking for an ML role where I can build and deploy end-to-end predictive models, strengthen feature engineering and optimization, and evaluate performance with strong metrics—using real data to solve impactful problems.

I’m an aspiring AI and machine learning engineer and data scientist pursuing B.Tech in Computer Science & Engineering, focused on building end-to-end machine learning and deep learning applications using the Python ecosystem. I specialize in EDA, statistical analysis, feature engineering, predictive modeling, and database integration, with an emphasis on model optimization and clear evaluation.

In my projects, I’ve developed a predictive recommendation system for MHT-CET college and course prediction using historical exam data, including automated data cleaning and a cloud deployment to a live AWS production environment. I’ve also built an end-to-end clinical risk assessment app (including preprocessing, feature engineering, training, and web deployment) and a smart bank loan approval prediction system using structured pipelines and tuned predictive classifiers. I enjoy using tools like Tableau, Power BI, and advanced Excel to translate insights into decisions while staying rigorous with metrics like Accuracy, Precision, Recall, F1-Score, and ROC-AUC.

Experience

Work history, roles, and key accomplishments

Intelligent Healthcare Risk

GitHub

Built an end-to-end machine learning clinical risk assessment app with preprocessing, feature engineering, model training, and web deployment. Evaluated models using Accuracy, Precision, Recall, F1-Score, and ROC-AUC with approaches such as Random Forest and XGBoost-style models.

Machine Learning data preprocessing Feature Engineering Model Training Deployment Random Forest XGBoost Evaluation Accuracy Precision Recall F1 Score ROC AUC predictive modeling

MHT-CET Predictor System

GitLab

Developed an end-to-end predictive recommendation system to project engineering colleges and branches using historical MHT-CET data and percentile scores. Built automated data cleaning and processing pipelines and deployed the model to a stable AWS production environment.

Predictive Analytics Recommendation Systems Data Cleaning Data Pipelines predictive modeling Machine Learning

Smart Bank Loan Approval

GitHub

Developed an end-to-end machine learning system for bank loan approval risk mitigation using structured preprocessing and engineering pipelines. Implemented predictive classifiers such as Random Forest and XGBoost-style models with hyperparameter tuning to mitigate overfitting and improve precision-recall balance.

Machine Learning data preprocessing Random Forest XGBoost Hyperparameter Tuning Overfitting Mitigation Precision Recall Evaluation

Intelligent Healthcare Risk

Render

Delivered a clinical risk assessment and patient diagnostic analytics web deployment for an end-to-end ML application. Used predictive architectures such as Random Forest and XGBoost-style models and reported ROC-AUC and classification metrics.

Deployment Machine Learning Random Forest XGBoost ROC AUC predictive modeling

Education

Degrees, certifications, and relevant coursework

Buddha Institute of Technology, Gaya

Bachelor of Technology (B.Tech), Computer Science and Engineering

2022 - 2026

Grade: CGPA: 7.92/10

Activities and societies: Ranked within the top 10% of the batch for core Machine Learning Foundations and Statistics courses; participated in an institute hackathon (24-hour schedule).

Pursuing a B.Tech in Computer Science and Engineering at Buddha Institute of Technology. Earned a CGPA of 7.92/10.