Hamza Ghannem

🧱 1. End-to-End Data Pipeline → Ingest Pharmaceutic data from AWS → Store it in Snowflake (via snowpipes) → Transform (snowflake dynamic tables, procedure & tasks) → Visualize in Power BI ⚙️ 2. Automate a Data Workflow → powerbi files filtering & item matching → Automate it with Python & powerbi API & openai api

∠ Participated in buiding a web platform for supply and demand of jobs in Tunisia ∠ Participated in the conferences & meeting with our client The Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) and our potential partners Ministry of ICT (Tunisia) , International Labour Organization(ILO) , the World Bank , INS and others (ANETI , CNS ...) ∠ Scraped most known jobs websites (python , selinium) ∠ Created preprocessing pipelines and automating the scraping from different websites ∠ Created interesting dashboards using plotly & dash , python ∠ Built machine learning models (forcasting) ∠ Automated comparison mathods (using R) to see the gap between data files

∠ Created python based programs to extract text data from pdf-files ∠ Extracted data from different table formats ∠ Preprocessed complecated unstructered text data ∠ Converted PDF contracts to TR (trade repository) format using python ∠ Used Natural language processing NLP to extract insights from text data ∠ Used Spacy and different machine learning approaches to deal with different matching and preprocessing tasks ∠ Debugged , assistance and Maintenance of the solution ∠ Solved complex problems and writing high quality python codes ∠ Prepared tasks and managing sprint goals ∠ Developed regression tests using pytest ∠ Created deep learning models for text classification and entity recognition (korean&English)

- Created a task automation virtual assistant which can recieve , understand and perform actions according to user (text/voice) messages. - Created a platform from which users can enhance the capability of their assistant by adding new training data , retrain the model and finally test it

∠ Created an HR Chat-Bot to be used by the clients of the company ∠ Ussed Microsoft Azure machine learning services to create the chatbot ∠ Used QNA-MAKER and LUIS services in the understanding part of our virtual agent ∠ Used Multiturn conversation feature in Azure bot service to ensure the efficiency of the conversation

∠ Configured and setting up the environment f or a network monitoring solution using Eyes of Networks & Nagios Supervisors. ∠ Created real time monitoring visualizations