Open to opportunities

Preet Pansuriya

@preetpansuriya

Message

AI/ML intern building predictive, NLP, and fraud-detection models with strong Python data-science fundamentals.

India

Message

What I'm looking for

I’m seeking an opportunity to apply my AI/ML and Python fundamentals to real-world problems, gain hands-on experience, improve my skills, and contribute meaningfully to innovative projects.

I’m a curious, results-focused AI & Machine Learning intern, applying my Python and data-science foundation to real-world problems. Across internships, I developed and evaluated supervised and unsupervised ML models, performing data preprocessing, feature engineering, and hyperparameter tuning using metrics like accuracy, precision, recall, and F1-score.

I also enjoy end-to-end delivery—building data pipelines, deploying predictive models with Scikit-learn, and supporting product decisions through dashboards and clear reporting. In fraud detection work, I handled class imbalance with SMOTE and improved Precision, Recall, and F1-score, and I bring the same rigor to NLP, energy optimization, and real-time computer vision projects.

Experience

Work history, roles, and key accomplishments

Data Science & ML Intern

BrainyBeam Info-Tech Pvt. Ltd.

Jan 2026 - Apr 2026 (3 months)

Performed EDA on large-scale datasets to extract actionable insights and trends. Built end-to-end data cleaning and preprocessing pipelines, developed predictive classification/clustering models with Scikit-learn, and created KPI-tracking interactive dashboards.

Data Pipelines Data Cleaning Feature Engineering scikit learn Classification Clustering Data Visualization Python

AI & Machine Learning Intern

InLighnX Global Pvt. Ltd.

Dec 2025 - Mar 2026 (3 months)

Built a credit card fraud detection system using Logistic Regression, Random Forest, and SVM, addressing class imbalance with SMOTE and feature engineering to improve precision, recall, and F1-score. Developed an energy consumption optimization model, and used Pandas, NumPy, Matplotlib, and Seaborn to visualize results and create technical reports.

Fraud Detection Logistic Regression Random Forest SVM Class Imbalance (SMOTE)Feature Engineering predictive modeling Data Visualization Python

AI & Machine Learning Intern

UPTOSKILLS

Jun 2025 - Sep 2025 (3 months)

Developed and tested supervised and unsupervised ML models using data preprocessing, feature engineering, and hyperparameter tuning. Evaluated models with accuracy, precision, recall, and F1-score, and collaborated to integrate models into applications.

Machine Learning Supervised Learning Unsupervised Learning data preprocessing Feature Engineering Hyperparameter Tuning Model Evaluation Python