Omar Faisal Mourad

Omar Faisal Mourad

Computer Science (AI) graduate and video editor

British national, based in Cairo, Egypt, and open to relocating

I build machine-learning systems that understand video, and I produce the videos people watch. First-Class Honours graduate from the University of Hertfordshire, AWS certified, and running YouTube and social media for TraderLion & Deepvue since 2024.

  • First-Class Honours, GPA 4.36 / 4.5
  • AWS Certified Cloud Practitioner
  • AWS Certified AI Practitioner
Portrait of Omar Faisal Mourad

About

I studied Computer Science with a specialism in Artificial Intelligence at the University of Hertfordshire and graduated with First-Class Honours. My coursework covered machine learning, computer vision, natural language processing, data science and software engineering, and my final-year project was among the highest-graded in my cohort.

Alongside the degree I built a second craft. Since February 2024 I've managed the YouTube channel and social media for TraderLion & Deepvue, a US trading-education company and its stock-research platform, editing broadcast-ready video in Premiere Pro and After Effects and shaping the content strategy.

I'm now looking for a role where I can put my technical background to work, along with the habit of delivering independently inside a remote, international team.

Based in
Cairo, Egypt
Nationality
British
Languages
English, Arabic
Open to
Remote, hybrid or on-site roles

Engineering projects

The system's output on a full match: every event it spots is labelled and cut into one summary reel.

Summarizing football matches with computer vision

Graduation project, among the highest-graded of the year

  • Computer vision
  • ResNet + PCA
  • Temporal models
  • Segmentation

A system that watches a full match and finds the moments that matter. It extracts frame features with a ResNet backbone reduced through PCA, then uses temporal sequence models and segmentation to spot multiple classes of event across all 90 minutes.

  • Image classification with CNNs

    CIFAR-10 and Fashion-MNIST, 20 classes

    Read the report

    A convolutional neural network that recognises everyday objects and clothing in one model. I merged CIFAR-10 with Fashion-MNIST, resizing and colour-matching the clothing images so both share one input format, then trained 11 convolutional layers with batch normalisation, dropout and data augmentation.

    87%

    overall accuracy on 20,000 unseen test images, across 10 CIFAR-10 classes and 10 Fashion-MNIST classes

    CIFAR-10

    • automobile0.93
    • ship0.90
    • truck0.90
    • horse0.87
    • airplane0.84
    • deer0.82
    • frog0.82
    • bird0.76
    • dog0.76
    • cat0.68

    Fashion-MNIST

    • trouser0.99
    • sandal0.98
    • bag0.98
    • sneaker0.96
    • ankle boot0.96
    • dress0.90
    • pullover0.88
    • t-shirt0.87
    • coat0.84
    • shirt0.72
    F1 score for each class, from the project's classification report.
  • Mental-health text classification

    NLP, bag-of-words, SMOTE

    Read the report

    Classifies students' social-media statements as normal or as showing signs of anxiety, depression or stress. After cleaning the text into bag-of-words features, I compared logistic regression with Naive Bayes, balanced the classes with SMOTE and tuned decision thresholds with precision-recall curves.

    92.6%

    accuracy on 7,957 unseen statements with logistic regression, the stronger of the two models

    • Logistic regression92.6%
    • Naive Bayes + SMOTE88.2%
    Test accuracy for both models, from the project's classification reports.
  • Conference management system

    Java, JavaFX

    Architected a system for speakers, attendees and scheduling, built on SOLID principles so it stays clean, maintainable and easy to extend.

  • Multi-agent Q-learning simulation

    Reinforcement learning, Q-learning

    Read the report

    Agents learn by trial and error to cross a 10×10 grid from one corner to the goal in the other, using Q-learning with epsilon-greedy exploration that tapers off as they learn. I compared a single agent with four agents sharing the grid, to see how competition changes the way they learn.

    1,000

    training episodes each for one agent on its own and for four agents learning side by side

    One agent

    Single-agent learning curve: total reward per episode rises from around -100 to near 0 within the first few hundred of 1,000 episodes, then stays there.

    Four agents

    Multi-agent learning curve: combined reward rises from around -400 to near 0 over the first few hundred of 1,000 episodes, then stays there.
    Total reward per episode, from the learning curves in the project's report.

Video work

TraderLion on YouTube

I run the channel end to end: editing, scheduling, channel branding and the overall content strategy, and I use viewer data to keep improving engagement and the production workflow.

Freelance client work

As a freelance editor I've cut videos for industry experts including Eric Worre, Chase McAllister, Scott McPherson and Luke Matthews.

Motion design

Launch films I've made for Deepvue's product releases. Browse through them, and tap or click a film to watch it with sound.

Testimonials

What clients have said about working with me.

Nick MassaVideo editing clientVideo testimonial
Keigan CarthyFounder, Vision ManagementVideo testimonial
Omar was a pleasure to work with, delivering all requested improvements swiftly – not to mention communication was a breeze and he paid attention to everything that was said. Highly recommend for any short-form video editing work.
@SatireExecutiveVideo editing clientSent on Discord
Working with Omar was an absolute pleasure! He knows what he's doing, is able to create a unique style for your videos and always delivers! I can only recommend working with him!
Jordan HassounVideo editing clientSent on WhatsApp

Experience

  1. Feb 2024 – Present

    Social Media & Video Editor

    TraderLion & Deepvue, remote (US)

    • Manage the company's YouTube and wider social-media presence, including content scheduling, channel branding and content strategy.
    • Edit and produce broadcast-ready video in Adobe Premiere Pro and After Effects, to tight deadlines.
    • Improved audience engagement by analysing viewer behaviour and streamlining the end-to-end production workflow.
    • Work across time zones with a distributed team.

    Channel I manage: youtube.com/TraderLion

  2. Sep 2025

    IT Support Intern

    TMG Group, Cairo

    • Worked with the enterprise IT department to diagnose and resolve hardware and software issues for staff across the organisation.
    • Supported network configuration and system maintenance, with first-hand exposure to enterprise IT infrastructure.

Education

2025, Hatfield, UK

BSc (Hons) Computer Science (Artificial Intelligence)

University of Hertfordshire. First-Class Honours with a cumulative GPA of 4.36 / 4.5.

2021, Cairo

A-Levels

Egypt British International School. A* in Computer Science, Physics, Chemistry and English; A in Mathematics.

AWS Certified Cloud Practitioner badge

AWS Certified Cloud Practitioner

Amazon Web Services, Foundational

AWS Certified AI Practitioner badge

AWS Certified AI Practitioner

Amazon Web Services, Foundational

Skills

Languages

  • Python
  • Java
  • C
  • SQL
  • JavaScript
  • HTML

Machine learning

  • TensorFlow
  • Keras
  • OpenCV
  • scikit-learn

Cloud and tools

  • AWS
  • Git
  • UML modelling
  • Data analysis

Video

  • Adobe Premiere Pro
  • After Effects
  • YouTube channel management

Let's work together

Hiring for an engineering or AI role, or need a video editor? Email me or book a free 30-minute call.

omourad713@gmail.com