Zaur Rasulov

• Developed intelligence-sharing dashboards, providing company-wide access to collected data.
• Designed customized data collection models for specific visualization tasks.
• Drafted strategic business intelligence roadmap, complete with data governance policies and tactical information safeguards.
• Responded to specific BI requests from personnel, creating data packets with requested information in easily understandable formats.
• Increased stakeholder satisfaction by presenting clear, concise, and insightful visualizations of complex data sets with more than 100 million data using MicroStrategy or Power BI.
• Provided ongoing support for end-users, troubleshooting issues with BI reports and ensuring timely resolution of problems.

• Gathered and processed more than 3 million of data using data engineering tools to ensure data quality and readiness for analysis
• Increased customer satisfaction by resolving complex issues and providing exceptional service at all times.
• Designed and developed the backend infrastructure of the website, ensuring its functionality and performance met the desired standards.

• Used Power BI, Tableau and Python to analyze conversion rates across 13 digital channels.
• Evaluated the effectiveness of marketing campaigns using advanced metrics and performance indicators.
• Translated conceptual customer requirements into functional requirements.

• Conducted thorough data validation and cleanup, ensuring accuracy and reliability of datasets used for analysis.
• Converted raw datasets into meaningful formats by performing extensive pre-processing activities such as normalization and transformation.
• Enhanced data visualization capabilities for better decision-making with the use of advanced BI tools.

Implemented data visualization techniques to effectively communicate insights to stakeholders.

• Identified, analyzed and interpreted more than 30 trends in complex data sets using supervised and unsupervised learning techniques.
• Utilized programming languages such as Python or R extensively throughout internship – applying relevant libraries and frameworks when appropriate.
• Optimized machine learning models for improved prediction accuracy and performance.