Mohamed Shaad

Data Scientist

Passionate and self-motivated data scientist with a robust foundation in data analysis, machine learning, deep learning, and generative AI. I've cultivated a comprehensive understanding of the data science field through online courses, hands-on projects, and continuous self-study.

In addition to my independent learning journey, I've honed my skills through valuable internships focused on data analysis, data pipeline development, and backend development. These experiences have provided me with practical insights and an enhanced ability to apply theoretical knowledge to real-world scenarios.

I possess a solid grasp of statistical concepts and am proficient in the Python programming language, utilizing popular data science libraries such as pandas, NumPy, and scikit-learn. My expertise extends to deep learning frameworks like TensorFlow, Keras, and PyTorch, enabling me to construct and train intricate neural networks for diverse tasks, including image classification, natural language processing, object detection, and generative modeling.

I excel in data cleaning, preprocessing, and exploratory data analysis, employing techniques like feature engineering and dimensionality reduction to optimize model performance. With a keen eye for detail, I have a strong ability to communicate complex technical concepts in a concise manner. My internship experiences have further enriched my skill set, making me adept at seamlessly integrating data analysis techniques, into broader data pipelines.

Currently, I am actively working as a data scientist, applying my expertise in machine learning, deep learning, and generative AI to tackle challenging problems and drive insights for my organization.