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yash rathore

@yashrathore3

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Data Scientist intern at SkillEcted who deployed three machine learning models and achieved 87% average accuracy.

India

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What I'm looking for

I’m seeking a Data Scientist role where I can solve high-impact business problems through predictive modeling.

At SkillEcted, I designed, trained, and evaluated more than eight machine learning models, achieving 87% average accuracy on datasets of more than 50,000 records. I also deployed three models to production.

I used supervised and unsupervised learning, including Random Forest, SVM, and K-Means, and improved performance over baseline models by 12%. My work included an end-to-end feature engineering pipeline across more than 20 features.

For my Credit Card Fraud Detection project, I built a classification pipeline using XGBoost and Random Forest, applied SMOTE to address class imbalance, and used SHAP to identify fraud-indicating features.

At Maincrafts Technology, I conducted exploratory data analysis on more than 100,000 records. I’m seeking a Data Scientist role where I can use predictive modeling to solve high-impact business problems.

Experience

Work history, roles, and key accomplishments

Python with AI Intern

EWB Courses

Aug 2026 - Sep 2026 (1 month)

Completed a 2-month AICTE-approved internship in Python with AI, strengthening core Python programming and applied AI/ML fundamentals. Delivered an assigned real-world project applying Python and AI concepts end-to-end.

Python AI Machine Learning

Data Science Intern

SkillEcted

Jan 2026 - Jun 2026 (5 months)

Designed, trained, and evaluated 8+ ML models including Regression, Classification, and Clustering algorithms, achieving average accuracy of 87% on datasets of 50,000+ records. Applied supervised and unsupervised learning techniques and executed end-to-end feature engineering pipelines.

Machine Learning regression Classification Clustering Random Forest SVM K Means Feature Engineering Data Cleaning Encodings Scaling Model Deployment

Data Science & Data Analytics Intern

Maincrafts Technology

Oct 2025 - Nov 2025 (1 month)

Conducted comprehensive EDA on 100,000+ records using Python (Pandas, NumPy, Matplotlib), identifying 15+ statistically significant patterns and anomalies. Analyzed data distributions, feature correlations, and class imbalances to inform feature selection and model architecture decisions.

Python Pandas NumPy Matplotlib EDA Statistical Analysis Feature Selection