Moustafa Ibrahim Email & Phone Number

Düsseldorf, North Rhine-Westphalia, Germany

● Tracked and analyzed key KPIs, including bounce rate, exit rate, add-to-cart ratio, and conversion rate, to quickly detect user journey issues by leveraging data from Google Analytics and Mapp Intelligence (Webtrekk). This early detection approach led to the resolution of bottlenecks and a 3% improvement in conversion rates.● Designed and refined a multi-point attribution model to improve the evaluation of marketing channels, providing more accurate insights into channel performance. This resulted in a 15% increase in marketing efficiency and a 2% uplift in lead generation by enhancing data-driven decision-making for campaign strategies.● Led A/B tests to assess the effectiveness of Campaign Ads on driving website traffic, analyzing traffic patterns and engagement metrics. Insights gained from these tests led to strategic channel adjustments, contributing to a 3% overall increase in order value and improved traffic flow.● Investigated the checkout funnel to identify and resolve user friction in the shipping provider selection and address pages by tracking user behavior and drop-off points. These optimizations led to a 5% increase in successful checkouts and a smoother user experience, enhancing the overall conversion rate.● Worked closely with the marketing team to optimize sorting rules on product listing pages by analyzing user interaction data. This resulted in a 3% increase in revenue, driven by better product visibility and user engagement.● Increased homepage engagement by 15% by analyzing click-through rates and user interaction with banners, then recommending changes to naming conventions and color schemes for better user attraction and content relevance.

Germany

● Implemented hands-on exercises, allowing students to master statistical methodologies, hypothesis testing, and regression analysis.● Supervised collaborative projects where MBA students leveraged statistical toolkits to analyze real-world datasets.● Guided students in interpreting data visualizations, emphasizing the importance of data storytelling and its impact on decision-makers.

Germany

● Design and development of a cutting-edge traffic light detection system leveraging the YOLOv8 algorithm.● Expertly customized the YOLOv8 algorithm to accurately identify and classify traffic lights through meticulous parameter tuning and model output optimization.● Technologies and Tools: YOLOv8, Python, Custom Annotation Tools, Model Evaluation and Optimization Techniques.

Germany

● Conducting statistical analyses to identify trends and patterns in traffic data● Creating visualizations and dashboards to help communicate complex data insights to non-technical stakeholders● Develop predictive models to forecast future traffic patterns and plan for infrastructure improvements● Collaborating with cross-functional teams to identify opportunities for process improvements and data-driven decision making

Online

● Data cleaning and preprocessing, ensuring data accuracy for further analysis.● Created interactive dashboards using Power BI for data visualization, improving data accessibility for non-technical stakeholders.● Conducted A/B tests to evaluate the impact of website changes, resulting in a 10% increase in user engagement.

● Utilized machine learning algorithms such as Random Forest and XGBoost to predict failures and optimize maintenance schedules.● Worked with cross-functional teams to gather and clean sensor data from the wellhead● Reduced downtime and maintenance costs by 20% by identifying and addressing potential issues before they occurred.

● Spearheaded analysis of customer behavior data, resulting in a 15% increase in customer retention rates.● Developed and maintained automated reports that improved operational efficiency by reducing reporting time by 30%.● Collaborated with the marketing team to analyze campaign data, leading to a 25% uplift in conversion rates.● Utilized Python and SQL to clean, transform, and manipulate large datasets for analysis.

● Utilized unsupervised machine learning techniques such as anomaly detection and clustering to identify fraudulent transactions.● Built a model using Amazon SageMaker and Python to predict the probability of a fraudulent transaction.● Utilized AWS services such as Amazon Kinesis and Amazon DynamoDB to handle and process large amounts of transaction data.● Collaborated with data scientists and engineers to implement the model in a production environment.● Improved the speed and accuracy of fraud detection by 20%, reducing financial losses for the company.

Master'S Degree, Computer Science, Excellent

Activities and Societies: ● Applied mathematical concepts using tools such as MATLAB and SciPy for numerical simulations. ● Implemented.

Intensive Training Program, Business Intelligence Specialist, Excellent

● Microsoft Business Intelligence Methodologies and Techniques (SSIS -SSAS-SSRS - DQS) ● Creating Advanced Dashboards based on Data.

Nanodegree, Data Analysis

● Completed Udacity's Nanodegree in Advanced Data Analysis, a comprehensive program covering the latest data analysis techniques and tools.

Computer Science Cs50

● Completed HarvardX's CS50's Introduction to Computer Science, a comprehensive introduction to computer science and programming ● Learned.

Petroleum Engineering

● Completed Bachelor's degree in Petroleum and Mining Engineering from (Suez University) ● Developed knowledge and understanding.