BWATNA KUYEMBO

Conducted a comprehensive customer churn analysis simulation for XYZ Analytics, identifying critical customer data points and formulating a strategic investigation approach.

Executed robust data cleaning, transformation, and analytical processes utilizing Python (Pandas, NumPy) to prepare datasets for advanced modeling.

Developed compelling data visualizations to effectively communicate complex trends and business patterns, enabling informed stakeholder decision-making.

Engineered and optimized a Random Forest churn prediction model, achieving a 50% recall rate in identifying at-risk customers.

Authored a concise executive summary report, articulating key churn drivers and providing actionable recommendations to mitigate customer attrition.

Collected, meticulously cleaned, and structured diverse datasets, ensuring high data accuracy and consistency for downstream analysis.

Performed in-depth Exploratory Data Analysis (EDA) and generated insightful charts/visual reports, providing critical data context for project teams.

Developed and implemented Python scripts, automating repetitive data processing and validation workflows, enhancing efficiency by an estimated 20%.

Collaborated on the development and rigorous testing of machine learning models, directly contributing to solutions for complex business problems.

Facilitated cross-functional collaboration with engineering and analytics teams, effectively translating data requirements into actionable insights.