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Hanae Nasar

@hanaenasar

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Data Scientist at Confidential Company building predictive models and end-to-end data analysis workflows.

Morocco

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At Confidential Company, I develop and refine machine learning algorithms for data-driven problems and build exploratory data analysis workflows, from assessing data quality to identifying patterns and exploring features.

At Yazaki, I developed an ensemble framework for demand forecasting and delay-risk assessment, achieving 89% forecast accuracy. I also engineered a local Qwen solution with retrieval-augmented generation to automate supply-chain workflows, reducing material activation processing from about three days to two minutes per request.

My projects include financial risk analysis, F1 race strategy modeling, and a RAG-powered financial document system. I’ve worked with tools including Python, FastAPI, LangChain, and MLflow to develop and deploy machine learning applications.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Confidential Company

Jul 2026 - Present (4 months)

Develop and refine machine learning algorithms to address data-driven problems and improve predictive performance. Build end-to-end exploratory data analysis workflows and evaluate model performance using appropriate metrics.

Machine Learning EDA Model Evaluation Python SQL

AI & ML Engineering Intern

Yazaki

Jan 2026 - Jun 2026 (5 months)

Analyzed historical sales and demand data across 18 manufacturing plants to identify demand patterns and address inventory imbalances. Developed a predictive ensemble learning framework combining XGBoost, LightGBM, CatBoost, and Random Forest, achieving 89% forecast accuracy. Engineered a local Qwen LLM solution with RAG to automate material activation processing, reducing processing time from ~3

XGBoost LightGBM CatBoost Random Forest Optuna RAG Qwen fastAPI Pydantic Lang Chain LangGraph SAP ServiceNow

AI & ML Engineering Intern

Wins

Oct 2025 - Dec 2025 (2 months)

Implemented LSTM-based time-series forecasting using Yahoo Finance data to predict stock-price movements across S&P 500 companies. Integrated financial news scraping, Transformer-based NLP, and FinBERT sentiment analysis to evaluate market sentiment and develop a personalized investment framework.

LSTM Time series Forecasting Yahoo Finance NLP FinBERT Sentiment Analysis Python

ML Engineering Intern

Smart Solutions

Jul 2025 - Sep 2025 (2 months)

Applied Principal Component Analysis for dimensionality reduction and implemented K-Means clustering for customer segmentation. Integrated the OpenAI API to transform customer segments into actionable business insights and targeted product recommendations.

PCA K Means Clustering Silhouette Score OpenAI API Python

Education

Degrees, certifications, and relevant coursework

Abdelmalek Essaâdi University

Master’s, Artificial Intelligence for Digital Economy & Management

2024 - 2026

Grade: Très Bien (16+/20)

Master’s in Artificial Intelligence for Digital Economy & Management with a focus on Data Science & Analytics, Machine Learning Algorithms, Predictive Modeling & AI Applications. Graduated with Distinction (Très Bien, 16+/20).