Layan Albelbisi

• Analyzed sales, customer behavior, and operational performance data for e-commerce and
restaurant clients.
• Built interactive Power BI dashboards to monitor KPIs, sales performance, and customer
engagement.
• Generated weekly and monthly reports to support business and operational decision-making.
• Used GA4, Adjust, and WebEngage to track customer journeys and identify growth
opportunities.
• Launched and monitored marketing campaigns across Meta, TikTok, Snapchat, and X.
• Analyzed campaign performance daily using GA4 and platform insights to optimize results
and improve ROI.

• Analyzed sales, customer, and product performance data for e-commerce businesses to
identify trends and growth opportunities.
• Built KPI dashboards using Metabase to track sales, orders, inventory, and business
performance
• Generated regular reports and insights to support data-driven decisions across sales,
marketing, and operations
• Conducted product and order performance analysis to optimize inventory planning and
improve operational efficiency

• Collected, cleaned, and analyzed large datasets related to childrens programs using Excel, Power
BI, and Infogram.
• Developed interactive dashboards and reports to support strategic decision-making.
• Automated data collection and visualization processes, reducing manual workload.
• Presented insights to internal teams, supporting operational and program monitoring strategies.

• Conducting a comprehensive mapping of child-relevant indicators from national and
international data sources.
• Establishing and maintaining a centralized database of indicators to support UNICEFs
monitoring efforts.
• Creating impactful data visualizations and dashboards using tools such as Power
BI, Infogram, and ArcGIS.

Analyzed large datasets related to children’s programs using Excel and Power BI.
• Developed interactive dashboards in Power BI and Infogram for data-driven decision-making.
• Automated data collection and visualization processes, reducing manual workload.
• Presented insights to internal teams to optimize operational strategies.

Built a Data Science job salary dashboard in Power BI, increasing visualization efficiency by 20%.
• Developed machine learning models achieving:
o Diamond Price Prediction: 97% accuracy, ranked 25th in Kaggle competition.
o Music Genre Classification: 93% accuracy, ranked 13th out of 54 in Kaggle competition.