Junior Data Analyst - Streamlined decision-making by developing interactive dashboards using Power BI and Tableau, allowing the management team to quickly assess key performance indicators (KPIs), reducing report generation time by 30%.- Optimized data processes, identifying inefficiencies in data cleaning and preparation workflows, which improved data accuracy by 15% and reduced processing time by 20%.- Collaborated with cross-functional teams to design and implement automated reporting solutions, cutting down manual report compilation by 50%, leading to faster response times in critical business decisions.- Extracted insights from complex datasets that supported marketing and sales strategies, leading to a 10% increase in client acquisition.- Trained new team members on data analysis tools and techniques, contributing to enhanced team productivity and cohesion.

Data Science Project - Led a team of four students in a predictive analysis project to forecast customer churn for a retail company, using machine learning techniques such as logistic regression and random forest.- Achieved 85% accuracy in predicting customer churn, which provided the company with critical insights to create targeted retention strategies.- Visualized complex data insights using Python libraries (Matplotlib, Seaborn), making the findings easily interpretable for stakeholders and non-technical team members.- Worked closely with stakeholders to define project scope and deliverables, ensuring alignment with business objectives and clear communication throughout the project.- Presented final results to an audience of peers and industry professionals, receiving recognition for clarity of analysis and actionable recommendations.