OUSSAMA ERRAFIF

Software engineer

oussamaerrafif@gmail.com | +212628859023 | AGADIR

Portfolio | LinkedIn | GitHub | HackerRank

Education

ENSA

G INFO Degree

CP GE

DEUG PCSI

EL FATH

Baccalaureat

AGADIR

Aot 2022 - Present

DAKHLA

Aot 2020 - Juin 2022

DAKHLA

2019 - 2020

ENSA

Fév 2024 - Mai 2024

Developed a Fleet Management System using Spring Boot, REST API, Hibernate, MySQL, and Maven for 100 vehicles.
Automated driver and vehicle assignment with algorithms, optimizing vehicle utilization by 25%, reducing fuel consumption and 20% reduced operational costs while ensuring regulatory compliance.

PFA | Full-Stack

Avril - Fév 2024 - Mai 2024

Developed a full-stack web app using Angular and NestJS, achieving 30% faster database rendering and 40% quicker backend responses.
Implemented secure JWT authentication, enhancing user data security and session management.
Used SendGrid for email with a 95% delivery success rate, demonstrating robust scalability.

Programming Languages:

JAVA, Python, PHP, JavaScript, Bash, Git, PL/SQL, C/C++

Libraries, Frameworks:

Spring, maven, React, redux, nodejs/djs, JEE

Tools / Platforms:

excel, MatLab, Linux, ORACLDB

Databases:

SQL, MongoDB

ResumeBuilderPy | Link

Python

Developed a Python-based tool for generating professional resumes using LaTeX.
Implemented customizable features allowing users to input their resume details directly into the Python script.
Utilized Jinja2 templates and user prompts.
Automated the compilation process, producing polished PDF documents with minimal user effort.
Reduced resume creation time by 70% compared to manual LaTeX editing.

NetScan | Link

Python/Nmap

Advanced Scanning: Implemented service detection, OS detection, traceroute, and banner grabbing across 50+ devices.
Parallel Scanning: Developed multithreading for 50% faster results and rate limiting to reduce network congestion by 30%.
Supported export formats like JSON, XML, and CSV for compatibility, enhancing the tool's integration capabilities with other systems.
Added an optional GUI and interactive network map, improving user experience and visualization of network data.

Machine Learning Rain Prediction Project | Link

Python, Scipy, Pandas

Data Collection: Gathered and processed 10,000+ weather data points from multiple sources.
Model Development: Built a robust machine learning model achieving 85% accuracy in rain prediction.
Performance Improvement: Optimized model performance, reducing prediction latency by 30%.