Enogho David

<p>Collaborated with cross-functional teams to design executive dashboards in Power BI and Streamlit, resulting in a 60% improvement in decision-making speed for a healthcare organization.<br>
Migrated legacy data pipelines to cloud infrastructure, Azure, for a financial services client, reducing data processing time by 60% and enhancing model deployment speed.<br>
Led customer segmentation analysis for a telecommunications company using R and SQL, enabling targeted campaigns that improved customer retention by 21%.<br>
Automated manual reporting processes using Excel and Python scripts, cutting down reporting time from days to hours and saving 12+ hours weekly for a logistics team.<br>
Advised a multinational consulting firm on cloud migration and model deployment using Azure ML, enabling the scalable deployment of machine learning models and achieving a 35% reduction in model inference time.</p>

- Collaborated with cross-functional teams to design executive dashboards in Power BI and Streamlit, resulting in a 60% improvement in decision-making speed for a healthcare organization.
- Migrated legacy data pipelines to cloud infrastructure, Azure, for a financial services client, reducing data processing time by 60% and enhancing model deployment speed.
- Led customer segmentation analysis for a telecommunications company using R and SQL, enabling targeted campaigns that improved customer retention by 21%.
- Automated manual reporting processes using Excel and Python scripts, cutting down reporting time from days to hours and saving 12+ hours weekly for a logistics team.
- Advised a multinational consulting firm on cloud migration and model deployment using Azure ML, enabling the scalable deployment of machine learning models and achieving a 35% reduction in model inference time.

<p>Analyzed large datasets using Python and SQL to identify performance gaps, contributing to a 17% improvement in key business metrics.<br>
Cleaned, transformed, and validated raw data using Python and SQL, ensuring 99% data accuracy for analysis and reporting.<br>
Applied statistical methods, including regression analysis and hypothesis testing, to support strategic planning and optimize key initiatives.<br>
Automated data collection and reporting workflows, reducing manual effort by 40% and accelerating insight delivery across departments.</p>

- Analyzed large datasets using Python and SQL to identify performance gaps, contributing to a 17% improvement in key business metrics.
- Cleaned, transformed, and validated raw data using Python and SQL, ensuring 99% data accuracy for analysis and reporting.
- Applied statistical methods, including regression analysis and hypothesis testing, to support strategic planning and optimize key initiatives.
- Automated data collection and reporting workflows, reducing manual effort by 40% and accelerating insight delivery across departments.

<p>Designed and deployed relational databases using SQL to support data analysis and reporting needs, improving data accessibility for analysts and reducing query response times by 30%.<br>
Defined user roles and streamlined data access workflows, ensuring timely delivery of relevant datasets to stakeholders and enhancing collaboration across departments.<br>
Implemented robust data security protocols and automated backup processes, achieving zero data loss incidents and maintaining 24/7 data availability.<br>
Facilitated organization-wide data literacy by conducting training on data querying and interpretation using SQL and Excel, leading to a 25% improvement in team efficiency when handling data requests.</p>

- Designed and deployed relational databases using SQL to support data analysis and reporting needs, improving data accessibility for analysts and reducing query response times by 30%.
- Defined user roles and streamlined data access workflows, ensuring timely delivery of relevant datasets to stakeholders and enhancing collaboration across departments.
- Implemented robust data security protocols and automated backup processes, achieving zero data loss incidents and maintaining 24/7 data availability.
- Facilitated organization-wide data literacy by conducting training on data querying and interpretation using SQL and Excel, leading to a 25% improvement in team efficiency when handling data requests.