Dania Muneer
Data Science & Machine Learning Professional
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About
My work focuses on Data Science & Machine Learning with hands-on experience in predictive modeling, computer vision, and NLP. Contributed to a SUPARCO-affiliated deep learning research project on satellite image restoration, including technical documentation and research reporting. Proficient in Python, SQL, TensorFlow, PyTorch, and Power BI, with a strong interest in building AI-driven, data-informed solutions.
Experience
Computer Vision & Backend Development Intern - SUPARCO
(2025-07 - 2025-08)
- Developed a YOLOv8-based computer vision model for aircraft detection using satellite imagery.
- Performed dataset labeling, preprocessing, augmentation, training, validation, and model evaluation.
- Built complete machine learning pipelines using Python, RoboFlow, and OpenCV.
- Applied deep learning techniques to solve real-world remote sensing problems.
Data Science Intern - CodeAlpha
(2026-01 - 2026-02)
- Developed machine learning models for car price prediction using regression, feature engineering, and exploratory data analysis (EDA).
- Built a SARIMA-based sales forecasting model for time-series prediction and trend analysis.
- Performed statistical analysis and visualization of unemployment datasets using Python.
- Utilized Pandas, NumPy, Scikit-learn, Statsmodels, Matplotlib, and Seaborn to analyze real-world datasets.
Data Operator (Contract) - CERP, World Bank
(2026-05)
- Entered, cleaned, and validated structured datasets in Microsoft Excel with high accuracy.
- Automated data processing using Excel formulas (IF, Nested IF, CONCATENATE, LEFT, UPPER, SUM).
- Standardized records and generated unique identifiers to improve data consistency.
- Prepared clean datasets and reports while maintaining confidentiality and data quality.
Education
Bachelor of Science (BS) - Physics - NED University of Engineering & Technology, Karachi