About me
Hey, I'm Aymane
Quantitative Data Scientist and ML Engineer with a double degree in Computer Science and Business, plus a master's in Quantum Information & Photonics from UPV Valencia. I've built ETL pipelines and dashboards at Amazon, won a pan-European data science challenge with Oliver Wyman, and done physics-informed ML research in optical imaging.
Now I'm carving my way into quantitative finance and agentic AI, applying the same mathematical rigor to markets and autonomous systems. I like hard problems, messy data, and first-principles thinking.
Experience
Research Intern
CVBLabs, UPV
- Designed and validated an optical simulation (FDTD + Mie theory): virtual test bench definition and experimental result interpretation.
- Built a Python pipeline for synthetic data generation and signal acquisition to train inverse models at scale.
- Used Docker to isolate execution environments and test model versions in parallel; Git-based version control in a shared repository.
Strategy Consultant / Data Science
Oliver Wyman, HackatOW
- Built a churn prediction model (XGBoost + logistic regression) achieving 80% precision and recall.
- Designed a data-driven retention strategy (€35k budget, 91.8% ROI).
- Winner of a selective pan-European challenge, first place against teams from top EU universities.
Business Intelligence Engineer, Intern
Amazon
- Built end-to-end ETL pipelines (Python, SQL, Amazon Redshift) to integrate and process logistics data at European scale.
- Developed real-time executive dashboards (Amazon QuickSight) to monitor transport KPIs, capacity, and route performance.
- Automated weekly logistics planning with Python scripts, achieving 98% scheduling accuracy and eliminating €500k in annual operational waste.
Data Manager
MAHLE Electronics
- Managed the migration of legacy ETL processes to SAP, ensuring data integrity across systems.
- Coordinated data flows between departments during the transition period.
Education
MSc in Quantum Information & Photonics
Sep 2025 - 2026Universitat Politècnica de València (UPV)
Grade: 8/10
Thesis: Physics-Informed Deep Learning for Quantitative Reconstruction in OCT
Double BSc in Computer Science & Business Management
Sep 2019 - Jul 2025Universitat Politècnica de València (UPV)
Grade: 9.9/10, Highest Honors
Two degrees, two theses. Computer Science Bachelor's Thesis: Real-Time Sign Language to Speech Translation. Business Bachelor's Thesis: Amazon Elderly data-driven marketing strategy (8.5/10)
Technical Skills
Languages
ML / AI
Back-end
Frontend
Data & BI
DevOps
Languages
Interests
Multi-agent systems, tool-calling architectures, and the future of autonomous software.
Portfolio optimization, Monte Carlo methods, and algorithmic approaches to markets.
Physics-informed neural nets, numerical simulation, and computational methods.
Workflow automation with n8n, scripting repetitive tasks, and building personal infrastructure.
Let's connect
Want to collaborate on a project, chat about AI, or just say hello? I'm always happy to hear from interesting people.
Get in touch →