M Mouaad AGOURRAM
Contact

Freelance Data & AI · France · Remote

MouaadAGOURRAM

Data Scientist and ML/AI Engineer. I build predictive models and RAG systems, fine-tune LLMs, and train teams to put AI to work.

open ./cv/mouaad-agourram --role data-scientist Contact me

Freelance, available for missions in France or fully remote.

Daily toolkit

Python PyTorch Scikit-learn TensorFlow Hugging Face LangChain MLflow
[ P ] Profile

Data Scientist focused on ML, GenAI and forecasting systems.

From framing a use case to evaluating the model, I cover the full ML lifecycle. Then I teach your team to run it without me.

What I do

Most of my work starts with a business question: what can we predict, and is it worth it? I design the experiments, train the models, and measure whether they deliver.

  • Predictive modeling on tabular and time-series data
  • Model evaluation, baselines and error analysis
  • RAG systems and LLM fine-tuning with LoRA / QLoRA
profile.json
{
  "name": "Mouaad AGOURRAM",
  "location": "France",
  "role": "Data Scientist / ML Engineer",
  "focus": ["ML", "RAG", "LLM fine-tuning", "Forecasting"],
  "availability": "Freelance / Remote / France"
}
[ E ] Experience

Applied machine learning, GenAI, and Data & AI training.

Three roles since 2024, one thread: take a model from first experiment to delivered result.

2025

Data & AI Trainer

Design and delivery of workshops in Data Science, Deep Learning and GenAI. Participants leave with working code, not slides.

2024 → 2025

Data Scientist · ML Engineer

Forecasting and audio ML systems built end to end: data preparation, training, fine-tuning and evaluation against business metrics.

2024

ML/AI Engineer · GenAI

RAG pipelines and LLM fine-tuning prototypes, with evaluation datasets to decide what ships and what stays a demo.

[ W ] Work

Selected projects with clear technical outcomes.

Five kinds of problems I keep coming back to: prediction, retrieval, tuning, audio and teaching.

[ S ] Skills

A focused stack for modeling, GenAI, and teaching.

A deliberately small toolbox: classic ML for tabular data, deep learning for the rest, and evaluation everywhere.

Core stack

Tools I use to train, evaluate, fine-tune and explain useful AI systems.

Python Forecasting PyTorch Scikit-learn TensorFlow Hugging Face LangChain FAISS MLflow 
$ cv skills --grouped

Machine learning:
  scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow

Generative AI:
  RAG, LangChain, FAISS, Hugging Face, LoRA / QLoRA

Forecasting:
  time series, fine-tuning, evaluation, MLflow

Training:
  Data Science, ML/AI, RAG, LLM fine-tuning
[ + ] Services

How I can help your team.

Freelance engagements in France or remote, from a scoped prototype to a full training program.

Data Science & ML

Frame predictive use cases, build models, evaluate performance and make results understandable.

RAG systems

Prototype retrieval workflows, vector search, evaluation datasets and answer quality checks.

LLM fine-tuning

Prepare datasets, fine-tune models, compare baselines and evaluate task-specific performance.

Practical team training

Hands-on sessions where your team builds and evaluates real models on its own use cases.