Ahmed Nasri

Project: Development of a digital twin generator in the healthcare sector: Design and implementation of a machine learning and data analysis platform for medical scenario simulation and prediction.

Tâches effectuées:

• • Business needs analysis and technical specifications writing.

• • Participation in the technical architecture design of the platform.

• • Development and deployment of high-performance and scalable REST APIs with FastAPI.

• • Relational database modeling and optimization under PostgreSQL.

• • Writing and execution of unit tests with Pytest, and implementation of continuous integration.

• • Code quality monitoring and maintenance via SonarQube and Bandit.

• • Clear and exhaustive technical documentation, accessible via Flasgger.

• • Integration of machine learning models into operational workflows.

• • Implementation of APIs for Long Running Jobs with DAPR.

• • Implementation of Publish/Subscribe mechanisms via DAPR for asynchronous and efficient processing of large tasks.

• • Version management of developed services with Git and coordination of team collaboration.

• • Close collaboration with the UX/UI team to ensure an optimal user experience.

Technical Environment: Python, FastAPI, Alembic, Poetry, DAPR, Microsoft Azure, DataBricks, Azure Storage, Docker, Bandit, SonarQube, Pytest, Pylint, Flake8, Git, Linux, PostgreSQL, JSON, REST API, Agile.

Development of a digital twin generator for the healthcare sector. Design and implementation of a platform integrating machine learning models and advanced data analysis functionalities for the simulation and prediction of medical scenarios.

Tâches effectuées:

• Business needs analysis and technical specifications writing.

• Participation in the technical architecture design of the platform.

• Development and deployment of high-performance and scalable REST APIs with Flask.

• Relational database modeling and optimization under PostgreSQL.

• Writing and execution of unit tests with Pytest, and implementation of continuous integration.

• Code quality monitoring and continuation via SonarQube, and Bandit.

• Clear and exhaustive technical documentation, accessible via Flasgger.

• Integration of machine learning models into operational workflows.

• Implementation of APIs for Long Running Jobs with DAPR.

• Implementation of Publish & Subscribe mechanisms via DAPR for asynchronous and efficient processing of large tasks.

• Version management of developed services with Git and coordination of team collaboration.

• Close partnership with the UX/UI team to ensure an optimal user experience.

Technical Environment:

Python, Flask, DAPR, Microsoft Azure, DataBricks, Azure Storage, Docker, Bandit, SonarQube, Pytest, Pylint, Flake8, Git, Linux, PostgreSQL, JSON, REST API, Agile.

Ensure the development and technical improvement of various applications on the "Open Vod" Services platform in terms of supervision, operational instructions, and technical administration.

Tâches effectuées:

• Refactoring and improvements of existing "Open Vod" service applications

• Gathering needs (incident, technical evolution) from the manager.

• Analyzing the request and/or debugging the problem.

• Development and implementation of solutions respecting good coding practices.

• Implementation of Unit Tests and validation.

• Writing update documents associated with new versions.

• Performing deployment steps in collaboration with operations teams, thus ensuring the deployment of new features.

• Development of REST APIs in Python/Flask.

• Development of a new web application based on the Microservices architecture in Python/Flask that manages all incident tickets or needs of different team members, as well as customer account management.

• Defining pipeline steps in the Gitlab-ci.YAML file

• Writing Dockerfile and docker-compose for the applications.