AHmEd GomaA
Cairo,Egypt
Overview
3
3
years of professional experience
4
4
years of post-secondary education
Work history
AI Engineer
Hyper Solutions
Riyadh
2024.01 - 2026.04
- Market Regime Detection System: Institutional clients faced heavy drawdowns due to static models failing during volatility shifts. I engineered an unsupervised HMM pipeline that reduced maximum drawdown by 18% through automated 'Risk-Off' triggers.
- Multi-Asset Alpha Generation: Asset managers struggled with high computation costs and poor correlation tracking across global ETFs. I developed a Multi-Output LSTM architecture that optimized infrastructure while capturing complex inter-asset lead-lag relationships.
- Ensemble Forecasting System: Trading desks reported inconsistent performance of individual models during market spikes. I built a Heterogeneous Stacking Ensemble that increased out-of-sample reliability by 12% and smoothed the equity curve.
Quant & Financial Engineer
WorldQuant University
2024.01 - 2026.01
- Geopolitical Risk Stress-Testing: Investment groups lacked quantitative methods to measure the impact of political shocks on energy prices. I designed a Bayesian Belief Network to model probabilistic shocks on Brent Crude, providing more accurate 'What-If' simulations.
- Strategic Factor Attribution: Pension funds needed to verify if managers provided true 'Alpha' or just expensive market-factor exposure. I conducted Fama-French 5-Factor analysis using robust regression to isolate true skill and optimize capital reallocation.
- MSc Financial Engineer
Data Scientist
UN
2023.03 - 2024.03
- Model Integrity & Bias Audit: Internal models showed 'phantom profits' in test environments that vanished in live trading due to data leakage. I built a Purged/Embargoed Cross-Validation system that identified and removed biased strategies before capital deployment.
- Visual Signal Detection: Analysts were overwhelmed by market noise, leading to missed entries and false signals. I implemented Gramian Angular Fields (GAF) to encode time-series into images for CNN pattern recognition, outperforming standard indicators.
- Signal-to-Noise Optimization: Research teams suffered from over-fitting as models captured statistical noise rather than true drivers. I deployed a denoising pipeline using the Marcenko-Pastur Law to extract stable eigenvalues, ensuring accuracy across historical cycles.
- Remote Internship
Education
Master's - Financial Engineering
World Quant University
Washington, D.C., US 2024.01 - 2026.01
Data Science Certificate - undefined
Explore AI Academy
2022.01 - 2024.01
Bachelor's - Communication Engineering
MSA University
Giza, EgyptBachelor of Science - undefined
University Of Greenwich
London, UKSkills
- Technical skills
- Machine Learning and Deep Learning (TensorFlow, PyTorch, Scikit-Learn)
- Data Analysis and Data Visualization (Pandas, NumPy, Matplotlib, Seaborn)
- Power BI
- Natural Language Processing (NLP)
- Financial Modeling and Quantitative Analysis
- Algorithm Development and Optimization
- SQL
- Python
- Time Series Forecasting and Trading Strategies
- Soft skills
- Problem-Solving & Critical Thinking
- Communication & Collaboration
- Adaptability & Continuous Learning, Stay updated
- Leadership & Decision-Making
LANGUAGE
Arabic: First Language
English: C1 Advanced
Timeline
Master's - Financial Engineering
World Quant University
2024.01 - 2026.01
AI Engineer
Hyper Solutions
2024.01 - 2026.04
Quant & Financial Engineer
WorldQuant University
2024.01 - 2026.01
Data Scientist
UN
2023.03 - 2024.03
Data Science Certificate - undefined
Explore AI Academy
2022.01 - 2024.01
Bachelor's - Communication Engineering
MSA University
Bachelor of Science - undefined
University Of Greenwich