Oussama NIDHAMMOU

• Designed and implemented a data pipeline for collecting and processing TV usage data via Google Cloud Platform (GCP). • Stored and transformed data in BigQuery using Cloud Functions. • Built SQL data models for TV data sources using dbt. • Collected, cleaned, and prepared usage data from Orange TV services. • Developed machine learning models to analyze data and predict usage trends. • Created and automated dashboards in Power BI to enhance visualization and support decision-making. • Monitored and managed capacity dashboards related to TV services. Technologies used: Power BI, SQL, Python, dbt, GCP (BigQuery, Cloud Functions), Git, Jupyter, Pandas, Scikit-learn.

• Collected information, performed profiling, and conducted risk analysis related to money laundering and terrorist financing. • Developed and updated sector-specific risk maps for AML/CFT. • Created national typologies for anti-money laundering and counter-terrorist financing. • Established operational procedures for handling suspicious transaction reports. • Automated processing and monitoring of UN Security Council resolutions using workflows (Airflow). • Implemented a risk analysis and predictive scoring system on AWS. • Prepared and transformed large-scale data using Apache Spark for model training. • Trained scoring models on Amazon SageMaker to detect money laundering risks. • Stored and transformed data in Snowflake for advanced analysis and model training. • Deployed predictions serverlessly using AWS Lambda and stored results on Amazon S3. • Visualized and reported results using Amazon QuickSight. Technologies used: AWS (SageMaker, Lambda, S3, QuickSight), Snowflake, Apache Spark, Airflow, Python, SQL, Pandas, Scikit-learn.

🚀 Advanced Web Scraping Implementation | 📊 Sentiment Analysis Tool 🔹 Engineered and deployed a comprehensive web scraping platform, employing advanced technologies to gather and organize diverse data from online sources. 🔹 Led the development of a robust sentiment analysis tool, applying sophisticated natural language processing techniques to extract valuable insights from textual data.

💡 Leveraging Data for Decision Support | 📊 Statistical Analysis Mission: 🔹 Spearheaded the design and development of an overpayment reclamation application. 🔹 Formulated insightful statistical analysis to facilitate data-driven decision support. 🔹 Applied a robust skill set in JAVA, MySQL, and SAS to execute effective data management and analysis.

Mission: 🔹 Development of a tool facilitating efficient parcel sorting and distribution through scanning technology 🔹 Proficiency in utilizing POWERPAD for streamlined data management 🔹 Active engagement in optimizing the dispatch process 🔹 Daily monitoring of agents' performance using the "DAILY COURIER CHECKLIST"