MERCY NJERI WAINAINA

• Training machine learning model to predict lounge usage trends.
• Compiling comprehensive dataset to support analysis and model training.
• Evaluating findings and delivering presentations to stakeholders for informed decision-making.
• Reviewing lounge eligibility criteria, leveraging customer groupings to refine demand assumptions.
• Developing reusable lookup table and justification for application in future British Airways schedules.

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

Developing machine learning model to predict customer churn effectively.

• Leveraging R/Python for data analysis, visualization, and recommendation summaries.
• Analyzing transaction and customer data to identify trends and detect inconsistencies.
• Developing metrics and examined sales drivers to enhance sales performance insights.
• Defining metrics for selecting control stores, ensuring accurate comparisons.
• Conducting analyses of trial stores against controls for informed decision-making.
• Creating visualizations and distilled findings to craft strategic client recommendations.
• Structuring reports using the Pyramid Principles framework for clarity.
• Submitting comprehensive reports with data visualizations, key insights, and strategic advice.

• Selecting appropriate visuals to support data-driven narratives.
• Developing effective visuals to enhance communication of insights and analysis.
• Framing business scenarios to provide context for visual presentations.

• Creating dashboards using Tableau for data visualization.
• Analyzing client data to identify trends and insights.
• Applying forensic technology to enhance data accuracy and integrity.