Zeineb Jeljli

I’m a Data Science Engineering student with hands-on experience across backend development, machine learning, and data systems. I’ve worked on production-oriented analytics, combining ETL pipelines, statistical testing, and deployable ML models.

In my Data Analyst Intern role, I built a full-stack Django + React web application to collect and analyze student feedback for the Tunis institutional accreditation process. I also automated annual statistical reports using Python (Pandas), improving data quality and reporting efficiency.

As a Data Engineer Intern, I implemented advanced statistical tests (ANOVA, Wallis, t-test, Chi2, Pearson/Spearman) in a FastAPI backend for a survey analytics platform. I added exploratory analysis features like K-means clustering and PCA, and I containerized pipelines with Docker while managing PostgreSQL and MinIO S3 for scalable data engineering.

I’m equally focused on impactful ML work—my projects include an LSTM stock market prediction pipeline with real-time sentiment analysis (VADER NLP) and SHAP explainability, and a production-ready DriverGuard AI system using multi-stream CNNs for real-time driver distraction detection.