khaoula nadi

khaoula nadi

Data Science / AI Intern – OCP Group @ OCP Group

Country

Morocco

City

Casablanca

Industry

Information Technology & Services

Skill

Long Short-term Memory (LSTM), XGBoost, Streamlit, NumPy, Data Visualization, Python (Programming Language), Machine Learning, Financial Analysis, Random Forest, Anomaly Detection, Spring Boot, Keycloak, Brevo, Back-End Web Development, Fraud Detection, Pandas (Software), Statistical Modeling, Systems Modeling, Arabic, Jupyter

Experience

OCP Group

Data Science / AI Intern – OCP Group

OCP Group

LinkedIn
2025-1 - 2025-6 · 6 mos

El Jadida, Casablanca-Settat, Morocco

Internship Worked on a national-scale drought monitoring and prediction project for Morocco in a context of limited country-specific open data availability. Extracted and processed environmental and climate data (2014–2024) using Google Earth Engine (GEE) and global datasets such as MODIS, CHIRPS, and ERA5. Engineered key environmental features including precipitation, evapotranspiration, NDVI, VCI, soil moisture (multi-depth), temperature, relative humidity, and SPI drought index. Developed LSTM deep learning models to forecast environmental variables over time. Applied XGBoost to predict the Standardized Precipitation Index (SPI) for regional drought risk assessment. Evaluated models to ensure robustness and reliability of drought predictions. Built an interactive Streamlit dashboard for real-time visualization of drought indicators across Morocco, supporting water resource management and decision-making. Tools & Technologies: Python · Google Earth Engine · MODIS · CHIRPS · ERA5 · LSTM · XGBoost · Streamlit · Pandas · NumPy · Data Visualization

Saphir Systems

Artificial Intelligence Intern – Saphir System

Saphir Systems

LinkedIn
2024-8 - 2024-9 · 2 mos

Casablanca, Casablanca-Settat, Morocco

Remote Internship Worked on a credit card fraud detection system during a remote internship, collaborating in a distributed team environment. Addressed a real-world limitation of labeled data by introducing a “suspicious transaction” category in addition to fraud and non-fraud. Designed and implemented an anomaly detection approach using Random Forest to identify suspicious transactions for manual review. Developed a classification model (Random Forest) to validate and categorize transactions after review. Built a secure web application using Spring Boot to operationalize the fraud detection system. Integrated Keycloak for authentication and access control. Implemented real-time email notifications for managers using Brevo when suspicious activity was detected. Strengthened skills in machine learning, backend development, security integration, and remote collaboration. Tools & Technologies: Python · Random Forest · Machine Learning · Spring Boot · Keycloak · Brevo · Backend Development · Fraud Detection

Education

Ecole Marocaine des Sciences de l'ingénieur

Ecole Marocaine des Sciences de l'ingénieur

LinkedIn

in Computer Science – MIAGE Option

2022-9 - 2025-7 · 2 yrs 11 mos
Ecole Supérieure de Technologie de Casablanca

Ecole Supérieure de Technologie de Casablanca

LinkedIn

Computer Science

2020-9 - 2022-7 · 1 yr 11 mos
Ecole Supérieure de Technologie de Casablanca

Ecole Supérieure de Technologie de Casablanca

LinkedIn

Computer and Information Sciences and Support Services

2020-9 - 2022-6 · 1 yr 10 mos
Ecole Supérieure de Technologie de Casablanca

Ecole Supérieure de Technologie de Casablanca

LinkedIn

Computer and Information Sciences and Support Services

2020-9 - 2022-6 · 1 yr 10 mos

khaoula nadi's Contact Information

Email

******@***.com

Phone

(**) *** ****

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