Data Scientist

I am a Data Scientist with a strong background in analyzing and interpreting large amounts of data to support better business decisions. I am skilled in using Python, SQL, and data visualization tools to clean, organize, and present information clearly. I have experience in building predictive models, identifying patterns, and creating reports that help teams understand trends and make smart choices. I am passionate about solving real-world problems with data and always eager to learn new tools and technologies to improve results.

Throughout my career, I have designed and implemented machine learning models to solve practical problems, such as detecting real and fake news using natural language processing techniques. I have hands-on experience with various machine learning algorithms including Logistic Regression, Random Forest, Naive Bayes, and Support Vector Machines. I am proficient in feature extraction methods like TF-IDF and word embeddings to enhance model accuracy.

I have developed web applications using frameworks like Streamlit and Flask to demonstrate real-time classification and prediction results. My technical toolkit includes Python, R, SQL, Jupyter Notebook, Google Colab, Git, and Excel. I am also experienced in data analysis and visualization using Pandas, NumPy, Matplotlib, Seaborn, Power BI, and Tableau.

In addition to my technical skills, I am a strong communicator and collaborator, capable of working effectively within teams. I am committed to continuous learning and applying critical thinking and problem-solving skills to deliver impactful data-driven solutions. I hold a Bachelor’s degree in Computer Science and Information Technology from the University of Swat, which has provided me with a solid foundation in statistics, mathematics, and database management.

I am currently based in Madinah, Saudi Arabia, and I am looking forward to contributing my expertise to organizations that value data-driven decision making and innovative problem solving.