نبذة عني
Detail-oriented Data Scientist with strong expertise in Python, SQL, and Machine Learning. Experienced in building predictive models, performing exploratory data analysis, and developing scalable data pipelines for data …
Detail-oriented Data Scientist with strong expertise in Python, SQL, and Machine Learning. Experienced in building predictive models, performing exploratory data analysis, and developing scalable data pipelines for data processing and analytics. Skilled in ETL, data wrangling, and deploying ML models using Flask APIs. Passionate about transforming raw data into actionable insights and data-driven solutions.
الخبرة
Designed secure authentication system using computer vision and ML (KNN)
Added multi-layer security with OTP and spoof detection
Built backend APIs using Flask and integrated MySQL database
Implemented data validation, processing pipelines, and user authentication flow
Built and compared ML models (Logistic Regression, KNN, Decision Tree, Gradient Boosting) on 2,000+ loan records
Performed feature engineering (DTI ratio, Loan Sanction Amount) to improve model performance
Evaluated models using Precision, Recall, F1-score, achieving ~80% accuracy with Gradient Boosting
Demonstrated improved performance of ensemble models for accurate loan approval prediction
Password Authentication System
Designed secure authentication system using computer vision and ML (KNN), Added multi-layer security with OTP and spoof detection, Built backend APIs using Flask and integrated MySQL database, Implemented data validation, processing pipelines, and user authentication flow
Developed CNN-based model using TensorFlow for image classification (38 disease categories), Performed image preprocessing and feature extraction using OpenCV, Built Flask-based web application for real-time predictions, Optimized model performance and improved prediction accuracy
Machine Learning
Built and compared ML models (Logistic Regression, KNN, Decision Tree, Gradient Boosting) on 2,000+ loan records, Performed feature engineering (DTI ratio, Loan Sanction Amount) to improve model performance, Evaluated models using Precision, Recall, F1-score, achieving ~80% accuracy with Gradient Boosting, Demonstrated improved performance of ensemble models for accurate loan approval prediction