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Computer Code Programming

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Freelancer Overview

I bring a unique blend of scientific domain expertise and AI-focused experience to data labeling and AI training projects, particularly in climate science, hydrology, and environmental data. With a strong academic background and over a decade of applied research, I have led and contributed to multiple projects involving the preparation, annotation, and quality control of climate and hydrological datasets, including satellite observations, reanalysis data, and ground measurements. My work has involved the development and evaluation of machine learning models, as well as the curation of training data for forecasting and simulation tools under changing climate conditions. In addition to my technical expertise, I offer advanced proficiency in English, French, and Arabic, allowing me to annotate, evaluate, and generate text across a wide range of scientific and policy-related domains. My experience as a peer reviewer and contributor to international climate assessments (including the IPCC AR6) has strengthened my skills in evaluating technical language, factual consistency, and domain alignment—key strengths when contributing to the training and fine-tuning of Large Language Models (LLMs). This interdisciplinary and multilingual capacity sets me apart in building reliable and context-aware AI systems.

Labeling Experience

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Work History