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Ayoub O.

Ayoub O.

Data Science · Entry-level

Available profile

Professional Overview

I am a recent engineering graduate in data science from ESI in Rabat, actively seeking job opportunities to further develop my skills and apply my knowledge in a professional setting. With a strong foundation in data analysis, machine learning, and MLOps, I am passionate about using data to drive impactful decision-making.During my academic journey and professional experiences, I have worked on a variety of projects, including time series forecasting, churn prediction, and natural language processing (NLP). I have also designed and implemented predictive models using Python, R, and SQL. My experience includes deploying machine learning models using Docker and Kubernetes, optimizing workflows with Kubeflow, and leveraging big data tools to extract actionable insights.I am proficient in handling large datasets, from cleaning and preprocessing to visualization and modeling, and have a deep understanding of various machine learning techniques. I am also skilled in using tools such as Scikit-Learn, TensorFlow, and Statsmodels. My curiosity, motivation, and diligence drive me to continuously seek out new learning opportunities, and I thrive in collaborative environments where I can communicate effectively with colleagues from diverse backgrounds.I am open to all internship opportunities in data science, machine learning, or related fields, where I can bring my technical skills and innovative mindset to make a meaningful contribution. If my profile interests you, I would be eager to discuss how I could support your company's data-driven initiatives.

Areas of Expertise

NLP & Prompt Engineering

Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.

AI & Machine Learning Engineers

Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.

data science & analytics

Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.

MLOps & AI Infrastructure

Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.

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