Omar Wael
Senior Data Scientist | Researcher at AUC | Software Engineer
Professional Summary
Results-driven AI, Data Scientist and Machine Learning professional with expertise in Generative AI, financial applications and Computer Vision, including Retrieval-Augmented Generation (RAG), fine-tuning, and time-series analysis. Proven track record in developing and deploying scalable ML solutions for Anti-Money Laundering (AML), customer segmentation, and ETL monitoring in banking.
Combines strong research background, contributing to academic papers in generative modeling and LLM applications, with hands-on software engineering experience in building secure backend systems, REST APIs, and payment integrations. Currently advancing AI research in skull auto-implant modeling and robotics while applying cutting-edge techniques to real-world financial and healthcare challenges.
Education
Master of Science (MSc) in Computer Science
Faculty of Science, Cairo University, Egypt
2024 – Present (in progress)
Thesis entitled "Adapting Generative AI techniques in financial domain"
Postgraduate Diploma of AI
Information Technology Institute (ITI), Cairo Egypt
2021
9 month program powered by school of engineering and computer science (EPITA), Paris, France
Bachelor of Science in Computer Science
Cairo University, Egypt
2014-2019
First Class Honors
Professional Experience
Data Scientist | Banking & Financial AI
06/2022 - Present (Full-Time)
• Architected transaction monitoring system
• Built risk models using supervised, unsupervised and Gen AI for 3 international banks
Machine Learning Researcher
06/2024 - Present
• Built models for skull implants (paper under journal review)
• Designed LLM RAG for robotics
Research Assistant
The American University in Cairo, Egypt
07/2024 - Present
• Built LLM pipeline for persona analysis
• Led multi-agent healthcare use cases
Software Engineer
12/2020 - 05/2022 (Full-Time)
• Built REST APIs and backend systems
• Deployed on DigitalOcean with payment integrations (Google Pay, Apple Pay, Stripe)
Software Engineer
11/2017 - 02/2019 (Full-Time)
• Developed RESTful APIs for e-commerce applications
• Integrated online payments (Fawry & bank cards)
Technical Skills
Programming Languages
ML/AI Libraries
Web Frameworks
Cloud & DevOps
Databases
Data Visualization
Key Projects
Generative AI for Anti-Money Laundering Scenario Generation
Designed and implemented a generative AI pipeline to automatically produce structured AML transaction-monitoring scenarios from textual descriptions. Utilized prompt engineering, fine-tuning, and RAG with a proprietary dataset of 133 real-world scenarios. Assessed outputs using domain-aware metrics including JSON schema validity, semantic similarity, and compliance suitability.
Machine Learning as a Service Platform for Banks
Developed a no-code ML/LLM pipeline builder for banks, enabling seamless data processing, model training, and deployment through an intuitive interface.
ETL Monitoring Tool
Built models for transaction-volume forecasting and anomaly detection, and deployed a Django dashboard for real-time ETL monitoring.
LLM-based Robotics Automation
Designing LLM pipelines for autonomous multi-robot task orchestration and natural-language command systems.
Bank Customer Segmentation
Developed unsupervised learning models to segment customers across multiple banks, improving targeting and operations.
Healthcare Persona Extraction using LLM
Applied prompt engineering and multi-agent pipelines to extract user personas from healthcare interview transcripts.
Research
Adapting Generative AI for AML Scenario Generation
Data Gear • 2024–Present
Researching how Large Language Models (LLMs) can generate structured Anti-Money Laundering (AML) scenarios from natural-language requirements. Developed a pipeline leveraging prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) to translate 133 real-world banking scenarios into JSON. Evaluating results on compliance alignment, semantic faithfulness, and hallucination risks.
Generative Modeling for Medical Implants
IStreamsLabs • 2024–Present
3D skull auto-implant generation; journal submission under review.
LLM-Assisted Thematic Analysis & Persona Extraction
AUC • 2024–Present
Prompt engineering and multi-agent LLM pipelines for qualitative research.
Recommendations
Omar combined technical expertise with clean, maintainable code and turned complex requirements into efficient features—an invaluable contributor to our product.
Talented data scientist with sharp analytical skills—always collaborative and supportive. Highly recommended.
Omar contributed key backend and frontend features to our AWASIS Science website. Technically strong, a clear communicator, and highly responsive to business needs. I’d gladly work with him again.
Organized, diligent, and a fast learner—Omar quickly understood market fit and delivered the right solutions. A pleasure to work with.
A fast learner, strong team player, and hard worker.
As TA for Data Visualization, Omar was deeply knowledgeable in Python for data work, offered clear feedback, and even ran extra coding sessions. One of the most helpful teaching assistants in the department.
An exceptional TA—explains SQL with detail and patience, and ensures everyone keeps up. I loved his teaching style.
Clear explanations, patience, and willingness to help—greatly improved my SQL understanding and confidence.
See all on LinkedIn: linkedin.com/in/omarwael
Professional Gallery
The American University in Cairo, Data Visualization course, where I served as Teaching Assistant and taught Python, Seaborn, and BI dashboards in Power BI and Tableau.
Sohag, Egypt, AI camp I organized and taught for students aged 10–14, covering Scratch, beginner Python, an introduction to What is AI?, and hands-on practice with popular AI tools.