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Assessing your cultural and operational fit
sowelni
June 11, 2026 – Present
Real-time Moroccan Darija Speech-to-Text transcriber and LLM assistant. Built with an Angular frontend, FastAPI Python backend, and a fine-tuned Qwen3-ASR model via streaming WebSockets. Fully containerized with Docker.
View ProjectEDA_Portfolio_Optimisation
June 1, 2026 – Present
Estimation of Distribution Algorithms for Cardinality-Constrained Portfolio Optimization
View ProjectIEX_LOB
May 28, 2026 – Present
based on the iex DEEP open data and cppparser lib, this is a ETL from extracting the LOB tables for DeepLOB architecture, saves tensor for deep learning use
View ProjectKairos
April 29, 2026 – Present
A deep-learning trading research stack that ingests raw exchange packets, learns to predict short-horizon price direction from the limit order book, and tests whether those predictions are tradeable — end to end, with an emphasis on honest evaluation over flattering numbers.
View ProjectTechJS
February 26, 2026 – Present
a various exercices for mastering JS concepts and frameworks(front and back)
View ProjectIoT-Intrusion-Detection
February 3, 2026 – Present
An intrusion detection system using the CIC-IoMT 2024 dataset to classify IoT network traffic as benign or malicious. This project implements a comparative study between classical Machine Learning and Deep Learning architectures to optimize detection accuracy.
View ProjectMongoDbOrderSimulator
January 7, 2026 – Present
MongoDbOrderSimulator — GitHub repository
View ProjectNotLibc
November 2, 2024 – November 26, 2025
NotLibc is a custom implementation of essential C standard library functions, built from scratch. It provides foundational utilities for strings, memory, I/O, character checks, numbers, and linked lists, allowing for easy handling of common C tasks without relying on the standard library.
View Projectopen-source-dataverse-events
September 14, 2024 – November 20, 2024
open-source-dataverse-events — GitHub repository
View ProjectCultural Fit Analysis
The candidate's portfolio showcases a strong inclination towards personal projects and self-directed learning, which can be a positive indicator for a culture that values initiative and continuous improvement. The range of technologies and problem domains explored suggests intellectual curiosity. However, the lack of team-based or collaborative project descriptions makes it difficult to fully assess cultural fit in a team-oriented environment. The target role 'Data Scientist' aligns well with the candidate's project focus on machine learning, data analysis, and quantitative finance.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and hands-on approach to learning and development. The diversity of projects suggests adaptability and a willingness to tackle various technical challenges. However, without psychometric test results or interview data, a comprehensive assessment of soft skills and operational fit is not possible.