Highly motivated data analyst with a strong background in data engineering, data analysis, and automation. Proficient in Python3, SQL, Google Suite, and Microsoft Office technologies. Demonstrated ability to build and manage scalable data architectures, develop data analysis chains, and create interactive data visualizations. Skilled at working independently and in team environments, with excellent problem-solving and project management capabilities. AWS Certified Data Engineer Associate, expertise with cloud platforms like Amazon AWS, S3, EC2, with a focus on data science applications and industry-relevant experience.
Data Mining Project: Clustering for Targeted Marketing Campaigns, Washington University of Science and Technology, Comprehensive Data Analysis Project, Designed and executed data analysis models and tools to enhance business and marketing strategies, focusing on customer segmentation, scalable AI/ML architectures, and market analysis., Developed customer segmentation models using Kaggle data, applying cluster analysis techniques (K-means and hierarchical clustering), which improved marketing campaign effectiveness., Created scalable data architectures to support AI/ML projects, for enhancing data processing efficiency., Conducted market analysis using Python and Jupyter Notebook, identifying key market trends and relationships, and developed predictive models with Scikit-Learn to forecast trends., Ensured data quality through rigorous preprocessing, including Z-score normalization and missing value handling., Designed and delivered data visualizations using Seaborn and Matplotlib., Collaborated with cross-functional teams to standardize data modeling, documentation, and reporting processes, improving overall data consistency and accessibility.
AWS Certified Data Engineer - Associate