Data & AI Engineering student at ENSA Al Hoceima · Analytics Consulting track
Open to Analytics & AI Consulting roles · Available 2026
I'm a final-year Data Engineering student at ENSA Al Hoceima (Morocco), obsessed with one question: what does this data actually tell us — and what should the business do about it?
Four years translating data into decisions: churn diagnostics for energy utilities, financial health scoring for 9,600 African SMEs, national connectivity demand modeling for Togo. Behind every insight — production pipelines on Azure Databricks, cloud-native platforms, and executive dashboards built to communicate, not just visualize. Two internships in applied AI confirmed that the hardest part is never the model — it's framing the right problem.
What makes me different: I bring engineering precision to consulting questions. I don't just build the analysis — I deliver the recommendation.
Co-built an end-to-end biometric AI platform for fingerprint classification & ridge counting across 12 classes. Sole implementer of the Human-in-the-Loop retraining system enabling continuous model improvement in production.
Applied research on 3D medical image segmentation. Implemented custom KAN layers integrated into a 3D U-Net — achieving +3% segmentation accuracy gain over the standard baseline on MRI datasets.
Each project structured as a consulting engagement: problem framed, approach rigorous, impact quantified.
PowerCo (energy utility) believed price sensitivity was the primary churn driver. BCG was asked to investigate and recommend a targeted retention strategy.
Reframed the hypothesis. Analyzed 14,600 customers + 193,000 pricing records. Engineered 50+ features. Benchmarked Random Forest, Gradient Boosting, XGBoost with rigorous CV.
Price is NOT the main driver — margin and customer segment are. Prioritize retention on low-margin, high-churn segments. XGBoost: ROC-AUC = 0.68, Precision = 0.96.
GFC needed to analyze hundreds of 10-K filings faster and extract strategic insights without manual reading.
Built a hybrid RAG engine (ChromaDB + SQLite). Extracted 2,000+ records from 34 companies × 3 years via SEC EDGAR. Engineered 20+ industry-benchmarked KPIs.
Production-ready system answering complex financial questions in seconds. Integrated Langfuse for hallucination eval + LiteLLM for failover.
SME lenders in Southern Africa needed to segment businesses by financial health to improve credit risk decisions.
Cleaned 9,618 records × 39 features across 4 countries. Engineered 47 features. Benchmarked 4 algorithms with stratified CV.
Gradient Boosting: F1 = 0.82 weighted, 78.7% accuracy. FastAPI scoring API deployed for real-time batch prediction.
The Togolese government needed to predict household internet uptake across the country to guide FTTH infrastructure investment decisions.
End-to-end ML pipeline on a national survey dataset (~14,400 rows, ~4,000 features). Strict data quality checks, PCA (350 components) for dimensionality reduction, combined with curated categorical indicators.
XGBoost selected: ROC-AUC = 0.86 on validation. Competition score: 0.7144. National-scale model guiding connectivity infrastructure priorities.
Selected projects demonstrating technical breadth — from AI agents to data platforms.
Automated scraping of Morocco data job listings (Indeed, ReKrute) with HDBSCAN clustering to segment archetypes and quantify skill demand. Power BI dashboards delivering prioritized skill gap recommendations.
Medallion lakehouse on Azure Databricks with real-time CDC via Debezium + Kafka and SCD Type 2 historical tracking. Optimized Delta tables via partitioning + Z-ORDER for scalable reporting workflows.
Production-ready AI assistant combining LangGraph agents with real-time tool usage via Model Context Protocol. Integrated GitHub, Supabase, Exa MCP servers. Evaluated with DeepEval. Deployed on GKE with Terraform + Prometheus.
Scalable healthcare data platform with ETL/ELT pipelines (Airflow + Airbyte), multi-layer dbt models (bronze/silver/gold), data quality checks with Great Expectations, and interactive dashboards in Superset.
Full-stack AI app generating descriptive captions from images using InceptionV3 encoder + LSTM decoder with attention mechanism. FastAPI backend with async file handling, React frontend with drag-and-drop and dark mode.
Engineer's Degree — Data Engineering
Integrated Preparatory Classes — Applied Mathematics
From raw ingestion to deployed models and board-ready recommendations.
Open to consulting internships and full-time roles in data analytics & AI.
Based in Morocco — open to relocate.