Profile

Machine Learning Engineer with experience in developing end-to-end ML solutions, including data preprocessing, model training, deployment, and monitoring. Skilled in Machine Learning, Deep Learning, MLOps, and data visualization with hands-on experience delivering production-ready AI applications using Python, FastAPI, Docker, and MLflow.

Education
Oct 2024 – Jul 2025Alexandria
Bachelor's Degree in Computer and Data Science with Business Analytics, Alexandria University (CGPA: 3.685/4.0 with Honors)⁠
Oct 2019 – Jun 2023Alexandria
Professional Experience
ISchool (Part Time)⁠, Coding Instructor (DECI Program)
  • •Taught Data Science and Advanced Programming concepts to students aged 12–18.
  • •Mentored students through hands-on coding exercises, projects, and problem-solving activities.
    • Jun 2026 – PresentRemote
  • •Monitored student progress and provided technical support and performance feedback.
    • Si-Ware Systems⁠, Machine Learning Intern
  • •Developed a calibration set and ML models to test FTIR spectrometer compatibility.
  • •Developed a pipeline to convert FT-NIR spectra data into image representations for deep learning models.
    • Jun 2025 – Oct 2025Hybrid

    Managed product backlog, collaborated with stakeholders, and ensured delivery alignment using Agile.

    Jan 2023 – Oct 2024Alexandria
    Teaching Assistant (Part Time)⁠, Computers and Data Science Faculty

    Supported teaching and lab sessions in programming and mathematics courses.

    Jul 2023 – Dec 2024Alexandria
    Projects
  • •Designed and implemented preprocessing techniques to clean, normalize, and structure spectral data.
  • •Built and evaluated CNN models versus PLS regression.

  • •Designed a complete ML pipeline to assess spectrometer compatibility using custom powder mixtures.
  • •Applied SNV preprocessing and PLS regression; evaluated using RMSE, R², and Bias metrics.
  • •Visualized spectral variance using PCA analyzed hardware effects on model accuracy.
  • •Developed a web-based dashboard using Flask, Dash, and XGBoost to predict annual rent in UAE cities.
  • •Enabled users to input property features and receive rent estimates via an interactive UI and REST API.
  • •Included EDA visuals and insights using Plotly, Pandas, and real estate market data.
  • •Created a real-time hand gesture recognition system with OpenCV and Scikit-learn.
  • •Trained five models using 3D landmarks; deployed Random Forest for best performance.
  • •Showcased ML in interactive human-computer communication.
  • •Created a real-time maze game controlled by hand gestures using webcam input and ML classification.
  • •Trained and deployed a Random Forest model via FastAPI for gesture recognition with Prometheus & Grafana monitoring. Combined JavaScript frontend with Python backend to enable interactive, hands-free navigation.
  • •Tools: Python, Scikit-learn, MediaPipe, FastAPI, JavaScript, Docker, Prometheus, Grafana
  • •Applied K-Means and GMM with Scikit-learn, PCA, and t-SNE for customer clustering.
  • •Conducted EDA to profile spending behavior and customer personas.
  • •Identified high-value customers with low credit limits for better targeting.
  • •Developed a time series model to forecast weekly Walmart sales using ARIMA and LSTM.
  • •Performed trend & seasonality analysis and planned deployment via Streamlit or FastAPI.
  • •Developed a web platform using Django, Python for stock prediction and portfolio creation.
  • •Analyzed stock trends and automated portfolio suggestions based on user preferences.
    • Skills
    Programming & Databases: Python | C  | C++ | SQL  | NoSQL (MongoDB)
    Data Visualization: Plotly | Power BI | Dash | Matplotlib | Seaborn | Feature Engineering
    Frameworks and Libraries: OpenCV | NumPy | Pandas | Scikit-learn | TensorFlow | Keras | Pytorch
    Cloud Computing: Docker | FastAPI | MLflow | Flask | MLOps | Azure | AWS | Pyspark
    Development Tools: GitHub | Jupyter | VS Code | Linux | Kaggle | Google Colab
    Project Management Tools: Agile Methodologies | Jira | Trello | Backlog Management
    Natural Language Processing: NLTK | spaCy | Word Embedding | Named Entity Recognition (NER)
    Time Series Analysis: Trend & Seasonality Detection | Forecasting | ARIMA | SARIMA | LSTM
    Certificates
    Volunteering Experience
    Member Media and Marketing, ESA
    Sep 2023 – Dec 2023
    HR Committee⁠, Project Engine HackerRank Campus Club, FCDS
    Sep 2023 – Nov 2023
    Sep 2022 – Jan 2023
    Languages
    Arabic: Native, English: Intermediate