> Markdown version of [/jobs/ext/4554393-data-scientist](https://www.wearedevelopers.com/jobs/ext/4554393-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Scientist

- **Company:** Veepee
- **Location:** Paris, France
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Python (Programming Language), Machine Learning, NumPy, Recommender Systems, Tensorflow, SQL Databases, Feature Engineering, Pytorch, Pandas, Scikit Learn, Xgboost
- **Published:** November 4, 2026
- **Apply:** https://fr.fashionjobs.com/emploi/veepee/Data-scientist,11105956.html

## About the Role

* Proficiency in Python (Pandas, NumPy, Scikit-Learn, etc.)Proficiency in SQL.
 * Foundational knowledge of Machine Learning.
 * Experience working with Machine Learning libraries (XGBoost, LightGBM, TensorFlow, PyTorch).
 * Solid understanding of statistics, evaluation metrics, and experimentation design.
 * Prior experience with recommender systems or e-commerce is a strong plus.
 * Strong verbal and written English communication.

## Description

The team focuses on implementing, maintaining, and continuously improving our recommender systems.

Today, we deliver personalized sales recommendations to millions of users in real time-and we're now scaling to include hundreds of thousands of products.

You will design and experiment with algorithms that power personalized recommendations across millions of users. Y

ou'll work with large-scale behavioral and product data to build models that increase engagement and conversion, collaborating closely with ML and Data Engineers to move your ideas to production., * Design, train, and evaluate recommender system models using state-of-the-art ML techniques.

 * Conduct in-depth data exploration and feature engineering to extract actionable insights.
 * Perform offline experiments and A/B tests to validate model impact on key business metrics.
 * Collaborate with ML Engineers to ensure smooth model deployment and monitoring.
 * Present findings and new approaches during Data Science Demos.