m
mohamedh02

Mohammed H

@mohamedh02

Data Scientist and AI Engineer

Territoires palestiniens
Anglais, Arabe
Certaines informations sont présentées en anglais.
À propos de moi
AI Engineering Intern at Kawkab, an applied AI firm serving MENA enterprises, where I build bilingual Arabic/English LLM products with Claude, OpenAI and Gemini APIs, FastAPI and React. Data Scientist with a Computer Engineering degree and a 660-hour ML bootcamp. I build ML models (churn prediction, PR-AUC 0.873), Arabic NLP (sentiment classifier, macro-F1 0.914), LLM apps and chatbots with guardrails, and Python data analysis and forecasting. Native Arabic, fluent English. Clear communication and clean, documented code.... Plus d’infos

Compétences

m
mohamedh02
Mohammed H
hors ligne • 

Voir mes services

Vision par ordinateur
I will build a machine learning model for your data in python
De90 $US / projetPlus de détails
Traitement automatique du langage naturel (NLP)
I will do arabic and english nlp and sentiment analysis in python
De90 $US / projetPlus de détails

Expérience professionnelle

Kawkab_AI

AI Engineering Intern

Kawkab AI • Temps partiel

Jul 2026 - Present • 3 mos

Part-time AI engineering internship at Kawkab, an applied AI firm serving MENA enterprises. I build bilingual (Arabic/English) LLM products end to end. - Kawkab Content Studio: bilingual marketing-copy generator in Next.js 15, React 19 and TypeScript, with validated API routes, a reusable brand-kit system, bulk generation of up to 10 variants, and a 15+ component design system. - Brand-compliance scoring endpoint that rates generated copy 0-100 against a brand's tone, values and approved facts, and returns itemized issues instead of pass/fail. - Bilingual content-generation MVP on FastAPI, SQLAlchemy and the Anthropic Claude API: tenant-scoped data model, approved-fact grounding, constraint validation with bounded auto-retry, and a mandatory human review queue, tested with pytest. - Client Scoping Assistant backend (TypeScript/Express, SQLite) in a 5-person team: gap analysis over a structured brief, question prioritization, multi-turn session state, and an API contract agreed up front so the frontend was built in parallel during a 1.5-day sprint. - AI student-support platform (fellowship final project, 2-person team): FastAPI/PostgreSQL backend, React frontend, Gemini assistant and OpenAI-based evaluator, Docker deployment.