MERCY NJERI WAINAINA

• Leveraging Python/R to analyze transaction and customer data, developing metrics and control–trial analyses to identify trends and evaluate sales performance.
• Creating visualizations and synthesizing insights into structured reports with strategic, data-driven recommendations.

• Compiling datasets and training machine learning models to predict lounge usage, refining eligibility and customer segmentation to improve demand assumptions.
• Evaluating results and presenting insights to stakeholders, developing reusable lookup tools to support future scheduling decisions.

Conducting data gathering and exploratory analysis to inform decision-making.

Developing machine learning model to predict customer churn effectively.