As a Data Analyst, I spearheaded data-driven initiatives that transformed business operations and enhanced decision-making processes. Leveraging my expertise in Python, Excel, SQL, Tableau, and Power BI, I played a pivotal role in turning complex data into actionable insights.

• Data Analysis and Reporting: Conducted comprehensive data analysis using Python and SQL to identify trends and patterns, resulting in a 20% increase in operational efficiency.
• Data Visualization: Developed interactive dashboards using Tableau and Power BI, enabling stakeholders to make data-driven decisions and improving reporting accuracy by 30%.
• Predictive Modeling: Built and deployed predictive models to forecast customer behavior, leading to a 15% increase in customer retention and a significant boost in revenue.

As a Junior Data Analyst at Exceptional Africalla (K) Ltd, I played a crucial role in supporting data-driven projects that enhanced business insights and decision-making. Utilizing my skills in Excel, SQL, and data visualization tools, I contributed to various analytical initiatives that drove operational improvements.

• Data Collection and Cleaning: Managed data collection and cleaning processes, ensuring data accuracy and integrity, which improved data reliability by 20%.
• Data Analysis: Performed detailed data analysis using Excel and SQL, identifying key trends and insights that informed strategic decisions.
• Process Optimization: Implemented new data management practices, reducing data processing time by 15% and enhancing overall data quality.
• Reporting and Visualization: Created comprehensive reports and visualizations using Power BI, enabling stakeholders to understand complex data more effectively.

As a Data Science Intern at EastAfrisat Communications, I gained hands-on experience in data analysis, machine learning, and data visualization. Working on real-world projects, I applied my knowledge of Python, SQL, and Tableau to deliver valuable insights and support data-driven decision-making.

• Data Visualization: Created visualizations using Tableau, presenting complex data in an easy-to-understand format for stakeholders.
• Research and Development: Conducted research on emerging data science technologies and tools, contributing to the development of innovative data solutions.
• Machine Learning: Assisted in developing and testing machine learning models, enhancing predictive capabilities and improving model accuracy by 15%.
• Data Analysis: Conducted data analysis using Python and SQL, contributing to projects that identified key business trends and opportunities.

Developed a machine learning model using historical data to predict crop yields based on various factors such as weather patterns, soil conditions, and agricultural practices. The model has been used to help farmers optimize their planting strategies and improve harvest outcomes.

Utilized unsupervised learning techniques, specifically K-means clustering, to segment customers based on purchasing behavior. The project helped an e-commerce business create personalized marketing campaigns to increase customer retention and sales.