Hamza Bouhdid

– Collection and consolidation of banking operations data from various sources, including websites and applications. – Cleaning, transforming, and standardizing raw data, ensuring accuracy and consistency before integrating it into the SQL database for optimal utilization. – Optimizing and structuring data into relational tables within the SQL database, ensuring logical organization and optimal accessibility. – Developing and managing complex SQL queries and stored procedures, enabling in-depth data processing and analysis to identify sensitive banking operations, high-error-rate branches, and customers with a high probability of fraud. – Designing and developing interactive reports in Power BI, integrated in real-time with the SQL database for efficient analysis and informed decision-making. – Utilizing DAX language to create advanced measures and functions, facilitating detailed and precise data analysis. – Leveraged predictive analytics and machine learning models (e.g., Random Forest, Kmean) to analyze branch error rates and customer behavior, identifying patterns and generating data-driven insights for process improvement and performance optimization. – Utilized Al-driven tools for monitoring branch performance and conducting in-depth customer behavior analysis using clustering and segmentation techniques, aiming to optimize processes and enhance the overall customer experience through personalized interventions.

– Aggregation of data from various sources, including websites and applications. – Preparation of raw data through cleaning and transformation processes, ensuring quality and smooth integration into an SQL database. – Design and management of advanced SQL scripts, including stored procedures to support in-depth data analysis. – Highlighting the company's strengths and weaknesses through dynamic reports created in Power BI. – Exploring sales data to detect patterns, prevent anomalies, and identify new opportunities. – Monitoring distribution channels to bridge gaps between the company and its distributors. – Providing actionable insights to management to facilitate informed strategic planning. – Analyzing customer behavior and feedback to propose tailored solutions that drive sales and enhance their experience.

– Development of an advanced mathematical model to minimize storage costs and reduce ship loading times. – Collection, cleaning, and transformation of data to ensure optimal integration into the model. – In-depth analysis of results to optimize scheduling procedures and improve production planning. – Significant reduction in machine downtime through data-driven decision-making. – Implementation of strategic raw material inventory management, enhancing operational efficiency.