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Veepee

Data Scientist

Paris, France

The employer does not state the work arrangement.

Apply on the employer's siteOriginal listingJSON

PeopleSeek Talent does not submit applications. The button opens the employer's own page; this listing was verified 3 hours ago.

PayNot listed
Work arrangementNot stated
Who can applyNot stated by the employer
LevelNot stated
TypeNot stated
Occupationdata scientist
LanguageNot stated
Posted25 October 2026
Last verified3 hours ago
StatusActive

About the role

Pioneer of online flash sales since 2001 and key player in European e-commerce, Veepee collaborates with over 7,000 brands to offer highly discounted products available for a limited time. Operating across various sectors, including fashion, home, wine, travel or beauty... Veepee achieved a turnover of 3.3 billion euros incl. VAT in 2024 and employs 5,000 staff members across 10 countries.

📄 JOB DESCRIPTION As a Data Scientist, you’ll join our Data Science team, distributed across Paris, Lyon, Barcelona, and Brussels. 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.
🎯 Responsibilities:
  • 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.

  • 👉 Requirements:
  • 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.

  • ✅ BENEFITS
  • Be part of a dynamic and international team!
  • Flexible schedule
  • Team buildings & afterworks

  • ⚙️ RECRUITMENT PROCESS
  • 1️⃣ HR Interview
  • 2️⃣ Technical Interview
  • 3️⃣ Team ITW
  • All our positions are open to people with health conditions or impairments. We are convinced that it is up to you to define the way you work, to develop yourself and to progress. At Veepee we guarantee that you can just be yourself! For the service of diversity and inclusion, Veepee is committed to reviewing all applications received on an equal basis. 🔗 COMPANY For more information about our ecosystem : https://careers.veepee.com/en/home-page-en/
    ❓ WHO WE ARE
    Veepeeᵀᵉᶜʰ is a tech community of 500 collaborators who play a key role in Veepee’s innovative strategy. From Warsaw to Sevilla, through Brussels, Amsterdam, Paris, Lyon, Nantes, Nice, Barcelona, Madrid and Lausanne all our projects are developed in an agile environment with a wide skills variety where you’ll be sure to find your place, no matter the technology you work with.If you love to try things why don’t you jump on this new adventure?
    Need more info > https://careers.veepee.com/en/
    Vente-privee.com processes the collected data to handle the recruitment process, and to evaluate your ability to carry out the job offered and your professional skills. You can learn more about our use of your data and your rights by reading our recruiting privacy policy.

    Find more English Speaking Jobs in France on Arbeitnow

    Skills

    Data

    Listed via Arbeitnow · first seen 25 October 2026 · last verified 28 October 2026

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