Jad Tounsi
Data ScientistI teach machines how to learn.
doctoria-solutions
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I teach machines how to learn.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
doctoria-solutions
Data Scientist
June 21, 2026 – Present
ai-website
August 3, 2025 – August 3, 2025
The Website That Doesn't Exist 🪄 it uses a Large Language Model (LLM) to generate and render entire web pages on the fly. Every request is routed through a configurable LLM provider, which creates the page content in real-time based on the URL you visit.
View Projecte-learning-dashboard-student
May 6, 2025 – May 12, 2025
e-learning-dashboard-student — repository
View Projectgemini-realtime-multimodal
December 22, 2024 – December 22, 2024
🤖 Gemini AI Chat + 🔄 Real-time WebSocket + 🖼️ Multimodal = Your next-gen chat app! Built with Google's Gemini AI for seamless text & image interactions in real-time. Fast, secure, and ready to deploy! ⚡️
View Projectocr-gradio-aimlapi
October 21, 2024 – October 22, 2024
📄 OCR Reader, 🔍 Analyzer, and 💬 Chat Assistant using 🔎 Zerox, 🧠 GPT-4o, powered by 🚀 AI/ML API
View Projectaimlapi-webscraper-agents
October 20, 2024 – October 20, 2024
🐝 Multi-Agent System for 🚀 ANY AI/ML Model: 🌐 Web Scraping & 📝 Content Analysis Powered by the 🔗 AI/ML API
View Projectllama3.1-nemotron-chatbot
October 17, 2024 – October 17, 2024
🦙💬 Building a Next.js Chatbot with NVIDIA Llama 3.1 Nemotron-70B Integration
View Projectopenai-swarm-webscraper
October 14, 2024 – October 17, 2024
🐝 OpenAI SWARM 🔍 Web Scraping Streamlit Web App and Content Analysis with Multi-Agent System
View Projectai-screenshot-organiser
October 12, 2024 – October 13, 2024
🦙 📹 PinataShot: Multimodal LLaMA 3.2 Screenshot Categorization on Pinata IPFS
View ProjectBinarized-Neural-Networks
February 26, 2024 – February 26, 2024
This project demonstrates the implementation and performance of a Binarized Neural Network (BNN) on the MNIST dataset, a collection of handwritten digits. BNNs are neural networks with binary weights and, in some cases, binary activations, making them computationally efficient and well-suited for resource-constrained environments.
View ProjectCultural Fit Analysis
The candidate's profile shows a strong inclination towards personal projects and exploration of cutting-edge AI technologies. This indicates a self-starter mentality and a passion for the field. However, the lack of diverse professional experience (only one current role listed with no details) and the absence of team-based projects make it difficult to fully assess cultural fit beyond individual drive. The 'experienceLevel': 0 suggests entry-level, which contradicts the 'Data Scientist' role and project complexity, making cultural fit assessment challenging without further context.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions suggest a proactive and innovative approach to problem-solving, but direct evidence of collaboration, communication, or stress handling is absent.