Education
- • Bachelor’s Degree in Software Engineering
- – Egyptian Chinese University, 2026
Data Analyst
Python • SQL • Excel • Power BI
Turning data into insights based on Results-driven, detail-oriented Analysis and, hands-on experience through dashboards, business intelligence, and clear storytelling. Transforming data into actionable decisions.

I don’t just build dashboards — I build decision systems. I specialize in transforming raw, messy data into clean, automated solutions that reduce manual work, improve reporting accuracy, and help businesses make confident, data-driven decisions. My focus is not just visualization, but clarity, performance, and measurable business impact.
Technical Skills
Power BI • DAX • Power Query • SQL • Excel • Python • Data Modeling
Business Skills
KPI Definition • Business Requirements Gathering • Dashboard Storytelling • Data-Driven Decision Support • Operational Efficiency • Performance Optimization • Financial Analysis • Industry Understanding • Storytelling with Data
Soft Skills
Problem-Solving • Attention to Detail • Communication • Time Management • Adaptability • Presentation Skills • Stakeholder Management
Pharmaceuticals Sales Performance Dashboard
Objective: Developed an interactive dashboard to monitor pharmaceutical sales performance, product distribution, and revenue trends across multiple categories and regions.
Outcome: Enabled clear visibility of top-performing products and revenue drivers, improved KPI tracking accuracy, and streamlined performance reporting for faster business insights.
Sales Analytics Dashboard
Objective: Designed a comprehensive sales dashboard to analyze revenue trends, customer behavior, and product performance across different time periods.
Outcome: Improved reporting efficiency through automated calculations and dynamic filtering, allowing stakeholders to quickly identify sales growth patterns and underperforming segments.
Financial Transactions Fraud Analysis Dashboard
Objective: Engineered a large-scale data pipeline (SQL + Python + Power BI) to analyze fraud trends across millions of transactions.
Outcome: Reduced raw data inconsistencies through SQL cleaning, automated fraud metric calculations, and delivered executive-ready dashboards highlighting fraud concentration patterns and behavioral risk indicators.
Maternal Health Risk Prediction (Machine Learning Project)
Objective: Designed and optimized multiple ML classification models to predict maternal health risk levels using real-world healthcare data.
Outcome: Improved minority-class recall using SMOTE and hyperparameter tuning, delivering a stable model with 87%+ accuracy, strong interpretability, and healthcare-ready insights.
“Professional, highly communicative, and delivered a data analysis solution that truly improved my workflow and decision-making!”
“Mohamed demonstrated outstanding problem-solving skills and attention to detail, delivering accurate insights on time and with exceptional quality.”