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I'm an AI and Data Science Engineer proficient in Python, SQL, and machine learning frameworks like TensorFlow and PyTorch. I'm passionate about leveraging NLP and computer vision to solve complex, real-world problems. I'm eager to apply my skills in data analysis, model building, and deployment to contribute to innovative projects.…

HDHILI BEN AYED

AI Engineer, Data Scientist, Programmer, +3

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I'm an AI and Data Science Engineer proficient in Python, SQL, and machine learning frameworks like TensorFlow and PyTorch. I'm passionate about leveraging NLP and computer vision to solve complex, real-world problems. I'm eager to apply my skills in data analysis, model building, and deployment to contribute to innovative projects.…

Available to hire

I’m an AI and Data Science Engineer proficient in Python, SQL, and machine learning frameworks like TensorFlow and PyTorch. I’m passionate about leveraging NLP and computer vision to solve complex, real-world problems.

I’m eager to apply my skills in data analysis, model building, and deployment to contribute to innovative projects.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

French

Advanced

Work Experience

AI Intern at Inherited Games Studio

July 1, 2025 - October 16, 2025

Developed an end-to-end NLP pipeline to analyze sentiment and key themes from a dataset of 500,000+ English and 100,000+ French video game reviews. Fine-tuned pre-trained BERT and DistilBERT models, achieving a 15% accuracy improvement over baseline models. Implemented data cleaning and pre-processing using Pandas and NLTK. Result: actionable insights into player preferences, reducing manual review time by approximately 80% and guiding future game development strategy.

AI Intern at Inherited Games Studio, Sousse

July 1, 2025 - October 16, 2025

Developed an end-to-end NLP pipeline to analyze sentiment and key themes from a dataset of 500,000+ English and 100,000+ French video game reviews. Fine-tuned pre-trained BERT and DistilBERT models, achieving a 15% accuracy improvement over baseline models. Implemented data cleaning and preprocessing using pandas and NLTK. Result: Provided actionable insights into player preferences, reducing manual review analysis time by an estimated 80% and influencing future game development strategies.