About
Data Scientist and Machine Learning Engineer with proven experience designing and deploying production-ready ML solutions across healthcare, computational biology, real estate, and economic domains. Built a pharmaceutical drug classification pipeline processing 60K records with 73% recall, engineered spatial topology features to decode 3D cancer organoid behavior across 8 biological conditions, and developed a house price prediction model achieving R² of 0.89 across 7 benchmarked algorithms. Skilled in Python, XGBoost, Scikit-learn, SHAP, SMOTE, and end-to-end deployment via Streamlit. Driven by a singular focus — turning raw, complex data into decisions that create measurable impact. Adept at translating complex, high-dimensional data into actionable insights through rigorous experimentation, model benchmarking, and intuitive deployments. Seeking a Data Scientist or Machine Learning Engineer role to solve challenging real-world problems with data-driven approaches.
Skills & Expertise (20)
Work Experience
Data Science Intern
Rubik's AI
Dec 2025 - Present
Built an end-to-end customer transaction prediction pipeline on a 200-feature anonymized banking dataset, handling severe class imbalance via SMOTE and RobustScaler preprocessing. Trained and compared 5 models (Logistic Regression, Random Forest, SVM, XGBoost, Tuned XGBoost), achieving ROC-AUC of ~0.87 and 66% recall on the minority class via RandomizedSearchCV hyperparameter tuning. Selected tuned XGBoost as the final model based on F1/recall trade-off analysis on an imbalanced binary classification task.
Education
B.Tech – Computer Science - GCOE Jalgaon, Dbatu University, Lonere
2023 - 2026 · Afghanistan
Certifications
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Skills (20)
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