ajayi babatunde

Leveraged Python and SQL to extract and transform data, driving a 20% increase in analysis efficiency and improving insight precision by 15%.
Performed data analysis to identify trends, which accelerated decision-making speed by 15%.
Created Power BI dashboards, which increased reporting efficiency by 25% and improved project delivery alignment by 15%.
Reconciled reports using Python libraries (Pandas, NumPy, Matplotlib, Seaborn), achieving 20% more precision across 4-6 projects and reducing errors by 10%.
Resolved data discrepancies, mitigating risks by 25%, and improving data accuracy to ensure reliable decision-making.
Streamlined reporting processes with Excel automation, cutting manual effort by 25% and optimizing data accuracy.

Leveraged Python and SQL to extract and transform data, driving a 20% increase in analysis efficiency and improving insight precision by 15%. Performed data analysis to identify trends, which Accelerated decision-making speed by 15%. Created Power BI dashboards, which increased reporting efficiency by 25% and improved project delivery alignment by 15%. Reconciled reports using Python libraries (Pandas, NumPy, Matplotlib, Seaborn), achieving 20% more precision across 4-6 projects and reducing errors by 10%. Resolved data discrepancies, mitigating risks by 25%, and improving data accuracy to ensure reliable decision-making. Streamlined reporting processes with Excel automation, cutting manual effort by 25% and optimizing data accuracy.

Developed a Python-based web scraping solution to extract e-commerce product listings from Jumia, leading to the collection of over 5,000 unique products and significant data insights for marketing strategies.
Created reports using advanced features of Power BI; findings identified the three biggest causes of customer churn within client portfolios, enabling targeted interventions to retain valuable users.
Modeled Power BI dashboards, improving client KPIs communication and boosting response time by 20%.
Reviewed HR data, identifying causes of gender imbalance and proposing solutions to increase female executive representation by 10%.
Remodeled data quality and consistency by 30% using Power BI, leading to accurate reports and better data-driven decisions.

Developed a Python-based web scraping solution to extract e-commerce product listings from Jumia, leading to the collection of over 5,000 unique products and significant data insights for marketing strategies. Created reports using advanced features of Power BI; findings identified the three biggest causes of customer churn within client portfolios, enabling targeted interventions to retain valuable users. Modeled Power BI dashboards, improving client KPIs communication and boosting response time by 20%. Reviewed HR data, identifying causes of gender imbalance and proposing solutions to increase female executive representation by 10%. Remodeled data quality and consistency by 30% using Power BI, leading to accurate reports and better data-driven decisions.

Executed a data science simulation for British Airways, showcasing data-driven strategies that refined operational efficiency by 25% and boosted customer satisfaction ratings by 15%.
Scraped and explored thousands of customer reviews, identifying key trends and sentiments, which provided actionable insights to improve service quality and enhance the customer experience.
Developed a predictive model using machine learning to forecast purchase behavior, optimizing marketing strategies and improving the accuracy of sales predictions by 20%.
Prepared and deployed machine learning models using Python and Power BI, elevating decision-making efficiency by 15%.
Led A/B testing and statistical analysis, amplified business strategy effectiveness by 25%.

Executed a data science simulation for British Airways, showcasing data-driven strategies that refined operational efficiency by 25% and boosted customer satisfaction ratings by 15%. Scraped and explored thousands of customer reviews, identifying key trends and sentiments, which provided actionable insights to improve service quality and enhance the customer experience. Developed a predictive model using machine learning to forecast purchase behavior, optimizing marketing strategies and improving the accuracy of sales predictions by 20%. Prepared and deployed machine learning models using Python and Power BI, elevating decision-making efficiency by 15. Led A/B testing and statistical analysis, amplified business strategy effectiveness by 25%.

Examined 7 datasets to identify key content trends for a social media client.
Increased client engagement by 15% through insights on top-performing content and user behavior.
Delivered PowerPoint and video presentations, speeding up decision-making by 20%.
Refined data quality by 30% with advanced cleaning techniques for more accurate analysis.
Extracted and analyzed data using SQL, producing interactive dashboards in Power BI and Tableau that bettered stakeholder decision-making by 25%.

Examined 7 datasets to identify key content trends for a social media client. Increased client engagement by 15% through insights on top-performing content and user behavior. Delivered PowerPoint and video presentations, speeding up decision-making by 20%. Refined data quality by 30% with advanced cleaning techniques for more accurate analysis. Extracted and analyzed data using SQL, producing interactive dashboards in Power BI and Tableau that bettered stakeholder decision-making by 25%.

Conducted data analysis and visualization to support key project initiatives, elevating efficiency by 20%.
Engineered machine learning models to address business challenges, increasing prediction accuracy by 15%.
Collaborated with cross-functional teams to ensure data integrity and accuracy, resulting in a 20% increase in the reliability of data insights.

Conducted data analysis and visualization to support key project initiatives, elevating efficiency by 20%. Engineered machine learning models to address business challenges, increasing prediction accuracy by 15%. Collaborated with cross-functional teams to ensure data integrity and accuracy, resulting in a 20% increase in the reliability of data insights.