Zainab Azzam

Data-driven and results-oriented business analytics and data science professional with a strong background in statistical modeling, predictive analytics, and machine learning. Adept at leveraging technologies like Python, SQL, R, and cloud-based platforms to extract meaningful insights, optimize decision-making, and drive business performance.

Experienced in data visualization, exploratory data analysis, and feature engineering to uncover trends, automate reporting, and improve operational efficiency. Passionate about applying advanced analytics to solve complex business problems and inform strategic initiatives.

Skilled in collaborating with stakeholders across various industries to translate business challenges into data-driven solutions. A proactive problem-solver with a strong analytical mindset, continuously seeking innovative ways to improve processes and enhance business intelligence.

Predictive Analytics Competition (Hotel Booking Cancellations)  Oct 2024

In a Predictive Analytics competition, I worked on developing a machine learning model to predict hotel booking cancellations. Using XGBoost, I optimized the model to achieve an AUC score of 0.94, making it the highest accuracy in the competition and securing second place overall. The project focused on analyzing customer booking behavior and implementing a dynamic pricing strategy combined with a tiered deposit system to reduce cancellations. This solution provided actionable insights for hotel revenue management, helping them minimize revenue loss and improve booking reliability.

Electric Vehicle Population Data Analysis  Dec 2024

This project explored three machine learning approaches—supervised, unsupervised, and mixed—to analyze Electric Vehicle Population Data. Using a Random Forest Regressor, I built a model that predicted EV range with 94.85% accuracy, identifying CAFV eligibility and vehicle type as the most influential factors. Additionally, I applied K-Means clustering to uncover regional EV adoption patterns, helping policymakers and infrastructure planners optimize charging station placements and incentive programs. A mixed approach combining clustering with supervised learning showed minimal improvement in prediction accuracy, reinforcing that clustering is more valuable for regional analysis rather than range prediction. The insights from this project can guide EV manufacturers, policymakers, and urban planners in making data-driven decisions.

Barbell Exercise Classification Using Sensor Data (In Progress) Feb 2025

This ongoing project focuses on classifying barbell exercises and counting repetitions using accelerometer and gyroscope data collected from MetaMotion sensors during gym workouts. The project involves data preprocessing, visualization, outlier detection, and feature engineering, followed by applying machine learning models such as Naïve Bayes, SVM, Random Forest, and Neural Networks. Rooted in the quantified self concept, this project aims to enhance fitness tracking applications by providing accurate movement classification and rep counting, benefiting both athletes and trainers looking to optimize their workouts through data-driven insights.

WE CARE WEB APP May 2020
We Care is a platform designed to provide a space for people to share their thoughts and be heard without judgment. It fosters personal growth through understanding and shared experiences. This project emphasizes the importance of human connection, focusing on providing a supportive environment for users. https://we-care-web.netlify.app/

UNIVERSITY OF NINEVEH APPLICATION PROTOTYPE Dec 2019
Developed an app prototype for the University of Nineveh using Flutter, aiming to centralize and streamline the university's news, updates, and important announcements for students, faculty, and staff. The prototype was well- received by university stakeholders and poised for full deployment. Unfortunately, the project was halted before completion due to COVID-19.

• Google Analytics Certification
• TradeDesk Marketing Foundations Certification
• CCNA
• TOT Business Development

• A+ graduation project with a score of 93%
• Conducting 2 Researches
• Writing +5 proposals and concept notes
• Implementing 4 projects
• Developing +5 Apps and Websites
• Establishing +5 Partnerships

• Iraq-Woman Entrepreneur of 2022 :

https://www.linkedin.com/posts/iraqi-innovators_iraq-tech-community-activity-7009180817113382912-eqnx/

• Google's Women Tech-makers Ambassador

• 9 female influencers you should follow on the Iraqi|KRI tech scene:

https://www.re-coded.com/open-study-hub/9-female-influencers-you-should-follow-on-the-iraqi-kri-tech-scene

• Meet Iraq's Influential Women In Tech – Version Two:

https://iraqtech.io/meet-iraqs-influential-women-in-tech-version-two/