Hamza Assemlali Email & Phone Number

Canada

Casablanca, Casablanca-Settat, Maroc

- Utilize SQL and Python to extract, transform and load (ETL) large data sets from various sources into a data warehouse, ensuring data accuracy and completeness.- Develop and maintain data pipelines and workflows to support data integration and processing using Python scripting.- Design and create interactive dashboards and reports using visualization tools such as Power BI and Tableau, enabling stakeholders to analyze key performance metrics and make data-driven decisions.- Conduct exploratory data analysis (EDA) and statistical modeling in Python to identify patterns, trends, and insights in complex data sets.- Collaborate with cross-functional teams to define data requirements and develop data-driven solutions to support business needs.- Perform data cleansing and validation using Excel and SQL to ensure data quality and integrity.Key achievements:- Implemented a new ETL(Extract, Transform, Load) process using python that reduced data processing time by 40%, enabling faster data-driven decision making across the organization.- Designed and developed a Tableau dashboard that visualized customer engagement metrics, resulting in a 15% increase in customer retention.- Developed a predictive model using machine learning algorithms in Python, which improved sales forecasting accuracy by 20%.- Streamlined the data validation process by creating custom Excel macros, reducing data validation time by 50%.

Casablanca-Settat, Morocco

- Collected and preprocessed a large dataset of facial expressions using Python and OpenCV, ensuring data quality and integrity.- Designed and developed a deep learning and Java-based system that detects the mood of a driver based on their facial expressions using convolutional neural networks (CNNs) and emotion recognition algorithms.- Conducted research to identify and evaluate state-of-the-art deep learning models and frameworks for facial recognition and emotion detection, including TensorFlow, Keras, OpenCV, and PyTorch.- Integrated the emotion detection system with existing driver assistance systems using python programming language, enabling real-time detection and alerting of potentially dangerous situations caused by driver's negative moods.- Collaborated with cross-functional teams, including hardware and software engineers, to ensure seamless integration of the emotion detection system into the overall driver assistance system.- Conducted rigorous testing and validation of the emotion detection system using various performance metrics such as precision, recall, and F1-score.Key achievements:- Designed and developed a robust and accurate deep learning-based emotion detection system that achieved a 95% accuracy rate in real-world testing, improving driver safety and satisfaction.- Successfully integrated the emotion detection model in Java-based desktop application.

Master 2 (M2), Big Data & Data Science

Licence, Informatics

Deust, Mipc