MD ZEESHAN UDDIN

• Data science enthusiast with a strong foundation in machine learning, data analysis, and predictive modeling.
• Certified in Data Science with distinction, and hands-on experience in developing data-driven solutions through a 6-month internship.
• Skilled in Python, data visualization, and statistical analysis, with a proven ability to deliver impactful projects, such as the Smart Insurance Cost Predictor and Customer Segmentation.
• Eager to contribute to innovative data science projects, and drive data-informed decision-making.

Data Science Intern, July 13, 2024 – January 13, 2025.

• Project 1: Smart Insurance Cost Predictor.
• Developed a machine learning model to predict insurance costs based on customer demographics, and health data.
• Utilized regression algorithms (Linear Regression, Random Forest) to achieve high accuracy.
  Cleaned and preprocessed data, performed feature engineering, and optimized model performance.
  Visualized insights using Matplotlib and Seaborn to present findings to stakeholders.
• Project 2: Customer Segmentation.
• Implemented clustering algorithms (K-Means, Agglomerative Clustering, DBSCAN Clustering) to segment customers based on purchasing behavior.
• Analyzed customer data to identify key segments for targeted marketing strategies.
• After comparing all three models, we found that K-means clustering is the best model, so we proceeded further with the deployment of this model using Streamlit.