Hamza Khader

Master of Science in Data Science

2022 - 2023

University of Sunderland, Sunderland, UK

Gained advanced knowledge in data science, covering statistical analysis, data manipulation, and end-to-end workflows. Developed strong programming skills in Python and R for analytical tasks, with practical experience in SQL for managing and querying databases. Studied specialized areas including Natural Language Processing (NLP) and Computer Vision, and acquired a solid foundation in Big Data technologies and cloud computing. The program integrated theory with real-world applications, preparing me to deliver data-driven solutions in diverse environments.

Bachelor of Engineering in Computer and Communications

2017 - 2022

Al-Zaytoonah University, Amman, Jordan

Provided a strong foundation in core engineering principles, focusing on computer systems, programming, and network communications. Developed technical skills in algorithm design, software development, systems analysis, and data structures, with additional coursework in mathematics and statistics. Gained expertise in embedded systems, operating systems, C++, Java, and database management. This interdisciplinary background in computing, electronics, and communication systems laid the foundation for my transition into Data Science, enhancing my problem-solving and analytical skills for data-driven challenges.

Freelance Data Analyst & Data Scientist

Feb 2025 - Present

Part Time (Remote)

• Collected, cleaned, and analyzed large datasets to identify patterns, trends, and actionable business insights.
• Built predictive machine learning models (classification, regression, clustering) to support data-driven decision-making.
• Designed interactive dashboards and visualizations (Power BI, Tableau, Python) to deliver insights to stakeholders.

Data Analyst & Scientist for Planning, Monitoring, and Research (PMR)

Oct 2024 - Sep 2025

UNICEF, Amman, Jordan

• Boosted data accessibility by 30% by developing and deploying interactive Power BI dashboards and infographics, enabling faster decision-making for global and local teams across 10+ countries.
• Consolidated 300+ indicators into a centralized Excel-based child/gender database by analyzing and mapping key sources (DHS, VAF, JMP), streamlining access and cross-sector analysis for program teams.
• Improved planning efficiency by 35% and accelerated project delivery by 25% through data validation and visualization using Power BI, Excel, and ArcGIS, enhancing stakeholder collaboration and reporting.

Data Scientist and AI

Apr 2024 - Sep 2024

Techno Hacks Edu Tech (Remote)

• Implemented predictive models: XGBoost for housing prices (R² = 0.91), SVM for diabetes detection (AUC = 0.84), and ensemble NLP classifier for sentiment analysis (89% accuracy).
• Executed full ML pipeline: EDA, feature engineering, scaling, tuning, and visualization (ROC, heatmaps, confusion matrix).
• Built high-accuracy ML models (Naive Bayes, Random Forest), achieving 99.8% in fraud detection, 96.6% in spam filtering, and 88.5% in sentiment analysis with GridSearchCV tuning.

Data Analytics and Career Development

Oct 2023 - Apr 2024

Correlation One - USA (Remote)

• Executed end-to-end data analysis projects using SQL, Python, R, Excel, Tableau, and Looker Studio, applying EDA, hypothesis testing, and CRISP-DM methodology to generate actionable business insights.
• Developed and delivered interactive dashboards, reports, and visualizations for stakeholders, enhancing decision-making processes.
• Applied problem-solving, critical thinking, attention to detail, and communication skills to support data-driven strategies and business intelligence initiatives.

Business Intelligence Analyst

Aug 2020 - Sep 2023

INCUBE FZCO - Jordan (Hybrid)

• Performed business analysis and managed datasets of up to 50,000+ records, applying SQL, Python, and ETL processes to enable predictive analytics and foundational AI applications.
• Designed and maintained interactive dashboards in Power BI, Tableau, Excel, and Looker Studio, delivering actionable insights that improved decision-making by 20% and operational efficiency by 15%.
• Collaborated with cross-functional teams, monitored KPIs, and developed simple predictive models using Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn), translating data into actionable business strategies.