Description

🚀 Data Scientist & AI Engineer | From Data to Business Impact

I help companies transform raw data into strategic insights and intelligent applications. My work combines Machine Learning, NLP, Generative AI, and Data Engineering to deliver solutions that are both technically robust and business-oriented.

With expertise in Python, SQL, Spark, LangChain, LangGraph, and cloud platforms (AWS, GCP, Azure), I design and deploy end-to-end pipelines that cover:

Data Engineering: ETL/ELT pipelines, real-time data streaming (Kafka, Spark), and optimized data warehouses (BigQuery, Snowflake, Redshift).

Artificial Intelligence & NLP: LLM-powered chatbots, retrieval-augmented generation (RAG), text-to-SQL, and predictive modeling.

Business Intelligence: Interactive dashboards, customer segmentation, churn prediction, explainable AI, and ROI optimization.

Deployment & MLOps: CI/CD workflows, containerization (Docker, Kubernetes), and cloud-native deployments.

🌟 Selected Achievements :

⚡ Cut SQL query latency by 50% with a multi-agent AI framework, accelerating business intelligence.

📊 Increased campaign ROI by 20% using advanced customer segmentation & RFM analysis.

🤖 Enhanced a mental health classification model with +25% F1 score through explainable AI.

Why Work With Me?

My strength lies in combining deep technical skills with a business-driven mindset. I don’t just build models or pipelines I ensure they generate real impact for your business, whether that means improving efficiency, reducing costs, or unlocking new revenue streams.

If you’re looking for someone who can bridge the gap between AI innovation and measurable business outcomes, I’d be glad to collaborate with you.

Languages

English
Native or bilingual
French
Fluent
Arabic
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

INTELCIA
Data scientist Intern
February 2025 - August 2025 (6 months)
Casablanca, Morocco
• Engineered a multi-agent LLM framework that combines a domain-specific knowledge graph with retrieval-augmented generation (RAG) to turn natural-language questions into optimized BigQuery SQL, cutting complex-query latency from 2 minutes to 1 minute (50%) and reducing routine queries from 45 seconds to 30 seconds (33%), unlocking true self-serve analytics.
• Automated the insight loop: text-to-SQL generation, result analysis, and visualization using Python, LangChain agents, OpenAI function calls, and BigQuery UDFs, reducing dashboard creation time for users from hours to minutes across internal teams.
• Delivered an interactive Chainlit interface with personalized authentication and memory, supporting granular responses, follow-up questioning, real-time result visualizations, and streamlined review of generated queries and user feedback.
Data Scientist LLM Generative AI Big Query Knowledge graph Agent IA
3D SMARTFACTORY
AI Research Intern
July 2024 - September 2024 (2 months)
Mohammedia, Morocco
• Designed a retrieval-augmented generation (RAG) engine enriched with knowledge-graph, increasing answer precision by 25% and accelerating research workflows.
• Developed an optimized multi-vector search pipeline leveraging FAISS and ChromaDB, cutting query latency on large-scale datasets by 30% while boosting recall.
Technocolabs Softwares Inc
Data engineer Intern
July 2023 - September 2023 (2 months)
Indore, Madhya Pradesh, India
• Optimized ETL workflows with Apache Kafka and SparkStructured Streaming, enabling continuous data ingestion and delivering near-real-time analytics in place of hourly batch runs.
• Built client-facing PowerBI dashboards that layer advanced analytics (DAX calculations, predictive visuals) on live data, transforming complex reports into intuitive insights and accelerating stakeholder decision-making.