Ahmed Khaled, Data Science Developer in Cairo, Cairo Governorate, Egypt
Ahmed Khaled

Data Science Developer in Cairo, Cairo Governorate, Egypt

Member since May 10, 2019
Ahmed is a senior data scientist who loves to dig into his clients' problems and solve them using state-of-the-art data-driven solutions. He can design, implement, and deploy data science solutions to solve problems, optimize outcomes, or automate a process. He's worked with both small and large scale businesses. He focuses on creating business opportunities to optimize the outcome. He educates, refines, and drives himself to be a better person.
Ahmed is now available for hire


  • SciMar One, LLC
    Python, Azure, Version Control, APIs, Databases, MongoDB, SQL, Pyodbc, Async...
  • Freelance
    Amazon Web Services (AWS), OpenCV, NLTK, Keras, Computer Vision...
  • Sports Vision Lab
    Python, Deep Learning, Machine Learning, Computer Vision, Version Control...



Cairo, Cairo Governorate, Egypt



Preferred Environment

Data Science, Shell, Linux, Matplotlib, Plotly, Keras, PyTorch, TensorFlow, OpenCV, Docker, GitHub, Apache Hive, SQL, Tableau, R, Python

The most amazing...

...program I've built forecasts product demand in a multi-branch store to create the best combination of products to put in the store and optimize revenue.


  • Python Back-end Developer

    2021 - PRESENT
    SciMar One, LLC
    • Developed the core logic of the website back end using Python and hosted on Azure.
    • Designed the database architecture for the website back end.
    • Designed several Azure Logic apps for curation functionality.
    Technologies: Python, Azure, Version Control, APIs, Databases, MongoDB, SQL, Pyodbc, Async, Web Scraping, Object-oriented Programming (OOP)
  • Senior Data Scientist

    2018 - PRESENT
    • Developed a program that takes a lung CT scan as an input and gives back numerical and visualization output of detected nodules in the scan, along with malignancy score, on the nodule level and patient level.
    • Developed a haircut and eyelashes recommendation system based on facial features and eye features; extended it to generate the photo of a human with the recommended changes, using GANs.
    • Developed a receipt OCR and text classifier to categorize the items inside the receipt to various classes.
    • Implemented a community detection algorithm, for academic purposes, to detect better design patterns for the UK railway stations.
    • Designed and built a tremor classification model based on 3D gyroscope acceleration readings.
    • Developed a snoring detection program built for medical purposes, this was built on AWS Sagemaker.
    • Built an ace percentage forecast model to forecast the number of aces that will be made by a player in ATP or WTP; it reached 0.4 total loss in it.
    • Developed a resume parser in Spanish and English, trained and deployed using AWS instances.
    • Developed a sentiment scoring model based on restaurant reviews (Yelp dataset).
    • Developed the RL agent based on Deep Q-Learning, to play Sichuan mahjong, along with creating a rule-based model to generate data acting as a start point performance, used SL to train on the generated data, and then RL to enhance the performance.
    Technologies: Amazon Web Services (AWS), OpenCV, NLTK, Keras, Computer Vision, Data Analysis, TensorFlow, Data Science, Git, Jupyter, Pandas, AWS, Machine Learning, Writing & Editing, Generative Adversarial Networks (GANs), Business Process Optimization, Natural Language Processing (NLP), Artificial Intelligence (AI), Deep Learning, Tableau, R, Python
  • Computer Vision / Deep Learning Engineer

    2020 - 2021
    Sports Vision Lab
    • Developed a soccer field registration module using Synthetic edge map dataset creation.
    • Developed a Player detection and tracking module using Deep Sort and Yolo.
    • Developed a Jersey number recognition module using super-resolution gans and deep learning.
    • Developed an unsupervised model to classify each player's team.
    Technologies: Python, Deep Learning, Machine Learning, Computer Vision, Version Control, Tracking, OpenCV, PyTorch, TensorFlow, Keras
  • Data Scientist

    2018 - 2019
    Synapse Analytics
    • Developed a cement market price daily forecasting, for a big cement firm, to reduce the loss of money between company and distributors, with ten days horizon; 91% of forecast values were within a 5% error margin.
    • Implemented a store assortment forecast to forecast the weekly demand of products and give the best combination of products to get the highest revenue possible; 90% of forecasts were within a 5% error margin. Built on an AWS EC2 cloud instance.
    • Developed a lot of presentations and dashboards for various projects using Superset, Tableau, and plotly.
    • Handled big databases, and maintained its structure, design, and data flow.
    • Worked on a clinic recommendation system, along with a time series forecasting model to predict when will be the next visit for a patient.
    Technologies: OpenCV, Keras, TensorFlow, Data Science, Git, Jupyter, Pandas, Machine Learning, Data Analysis, Data Visualization, Natural Language Processing (NLP), Computer Vision, Deep Learning, Tableau, R, Python


  • Simple EDA on Gun Usage Data Along with Census Data in the US (Development)

    This exploratory data analysis was done to study the relationship between the census data, and the portions of the population in the US with gun usage to get insights among them, and try to prevent or reduce this usage in the future.

  • Soccer Field Registration and Broadcast Analysis (Development)

    Designing and implementing a pipeline that takes a broadcast, performs:
    1. Soccer edge detection
    2. Player detection and tracking (with occlusion handling)
    3. Jersey number recognition
    4. Homography extraction (player mapping on the minimap)
    5. Player team classification
    6. Ball detection and mapping
    7. Homography sequence stutter removal using convex optimization

    All of it was done in Python, with free-custom-made datasets.

  • Arabic Sentiment Analysis (Development)

    This project aimed to retrieve the sentiment of an Arabic sentence scraped from Twitter regarding multiple subjects. The first trial was on COVID-19 related tweets, and then it was employed on other material like sports.

  • Optimizing Retailer Revenue with Sales Forecasting AI (Publication)
    Retailers often face supply and demand issues that cause them to miss out on potential sales or tie up a lot of money in overstocked products. In this article, Toptal Data Scientist Ahmed Khaled explains how retailers can boost revenues and cut costs with sales forecasts backed by artificial intelligence.


  • Languages

    Python, SQL, R, Java
  • Libraries/APIs

    Pandas, TensorFlow, Keras, PyTorch, NLTK, OpenCV, Matplotlib, Pyodbc, Async
  • Tools

    Jupyter, Google Analytics, Tableau, Git, LaTeX, GitHub, Plotly, Shell
  • Paradigms

    ETL, Object-oriented Programming (OOP), Data Science
  • Platforms

    Jupyter Notebook, Amazon Web Services (AWS), AWS Lambda, Azure, Docker, Linux
  • Storage

    PostgreSQL, MongoDB, Elasticsearch, Apache Hive, Databases
  • Other

    Artificial Intelligence (AI), Time Series Analysis, Modeling, Statistics, Data Engineering, Algorithms, Deep Learning, Machine Learning, Computer Vision, Business Process Optimization, Time Series, Medical Imaging, Data Visualization, AWS, Optimization, A/B Testing, EDA, Reinforcement Learning, Deep Reinforcement Learning, EMR, Biomedical Skills, Data Analysis, Big Data, Technical Design, Image Processing, Data Warehouse Design, Natural Language Processing (NLP), Generative Adversarial Networks (GANs), Data Warehousing, Genetic Algorithms, Decision Analysis, Forecasting, EHR, Writing & Editing, Tracking, Deployment, Integration, Version Control, APIs, Web Scraping, BERT
  • Frameworks

    Spark, Hadoop, Realtime


  • Bachelor's degree in Biomedical and Systems Engineering
    2013 - 2018
    Cairo University - Cairo, Egypt

To view more profiles

Join Toptal
Share it with others