Data-driven professional with over 5+ years of experience in data analysis, business intelligence and data engineering, transforming complex data into actionable insights and an MSc in Data Science and Artificial Intelli…
Data-driven professional with over 5+ years of experience in data analysis, business intelligence and data engineering, transforming complex data into actionable insights and an MSc in Data Science and Artificial Intelligence (1st). With a history of enhancing operational efficiency and business performance.
Build end-to-end automated analytics dashboards in Power BI and Tableau, enabling 50+ stakeholders to monitor KPIs, contributing to a 12% reduction in discrepancies.
Partner with finance, operations and engineering teams to restructure critical data models in Azure SQL, increasing reporting throughput and reducing weekly manual data preparation by 40%.
Lead troubleshooting and quality assurance of complex datasets using Databricks notebooks and SQL, cutting data integrity issues by 30% and improving SLA performance.
Automate reconciliation processes and recurring financial reports, saving the business 60+ hours monthly and enabling faster month-end close cycles.
Build end-to-end automated analytics dashboards in Power BI and Tableau, enabling 50+ stakeholders to monitor KPIs, contributing to a 12% reduction in discrepancies. Partner with finance, operations and engineering teams to restructure critical data models in Azure SQL, increasing reporting throughput and reducing weekly manual data preparation by 40%. Lead troubleshooting and quality assurance of complex datasets using Databricks notebooks and SQL, cutting data integrity issues by 30% and improving SLA performance. Automate reconciliation processes and recurring financial reports, saving the business 60+ hours monthly and enabling faster month-end close cycles.
Designed and implemented BI solutions combining Power BI, Tableau and SQL-based ETL to enhance customer segmentation accuracy and marketing analytics, leading to a 20% lift in campaign response rates.
Migrated over 40 legacy static reports into interactive dashboards, reducing reporting time by 60% and enabling real-time insight access for senior management.
Collaborated with engineering and CRM teams to standardize data flows across ERP, campaign and customer systems, improving data synchronization by 30%.
Built SQL-driven data validation frameworks and audit checks, reducing reporting anomalies by 25% and strengthening decision-making confidence across business units.
Designed and implemented BI solutions combining Power BI, Tableau and SQL-based ETL to enhance customer segmentation accuracy and marketing analytics, leading to a 20% lift in campaign response rates. Migrated over 40 legacy static reports into interactive dashboards, reducing reporting time by 60% and enabling real-time insight access for senior management. Collaborated with engineering and CRM teams to standardize data flows across ERP, campaign and customer systems, improving data synchronization by 30%. Built SQL-driven data validation frameworks and audit checks, reducing reporting anomalies by 25% and strengthening decision-making confidence across business units.
Engineered relational database architectures using PostgreSQL and MySQL Server, improving query performance and data retrieval efficiency by 15%.
Used Python in Jupyter Notebook for data preprocessing and cleansing, increasing dataset reliability by 20% and reducing downstream processing issues.
Developed a predictive model using Python to enable better planning and resource allocation for upcoming fundraising campaigns.
Collaborated with instructors and IT teams to identify analytical pain points, translating them into practical reporting solutions that improved data visibility and decision accuracy.
Engineered relational database architectures using PostgreSQL and MySQL Server, improving query performance and data retrieval efficiency by 15%. Used Python in Jupyter Notebook for data preprocessing and cleansing, increasing dataset reliability by 20% and reducing downstream processing issues. Developed a predictive model using Python to enable better planning and resource allocation for upcoming fundraising campaigns. Collaborated with instructors and IT teams to identify analytical pain points, translating them into practical reporting solutions that improved data visibility and decision accuracy.
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