We’re Adevinta, a global leader in digital marketplaces. Our household name brands, including Marktplaats in the Netherlands, mobile.de in Germany and leboncoin in France, reach hundreds of millions of people every month.
We’re all about matchmaking, and our sites help people find whatever they’re looking for in their local communities – whether it’s a car, an apartment, a sofa or a new job. Every connection made or item found makes a difference by creating a world where people share more and waste less.
Our brands are supported by global Tech Hubs in Barcelona, Amsterdam, Paris and Berlin. Their goal is to develop common global products and innovation platforms which all of our brands can use. This means using cutting edge technology to create highly scalable, customisable and secure products and components that free up development time and leverage our access to global data.
What you’ll do & Who you are
We are looking for a Senior Data Scientist to join our mission to make our platform an even safer place to trade. You will be responsible for designing, building, and continuously enhancing production-grade, end-to-end machine learning models that detect fraud and assess user risk in the Trust and Safety domain. You will be part of a cross-functional business area composed of multiple teams including experts from Product, Customer Service, Analytics, Data and Engineering. Together, you’ll tackle one of the most meaningful challenges in online platforms: building trust at scale.
This is your opportunity to improve the experience of millions of users and have an impact by building a platform that enables sustainable trade for everyone.
Your role:
- Understand fraud patterns, user trust needs and identify where Machine Learning can bring the greatest impact.
- Train and evaluation of ML models from scratch or fine-tune existing ones for fraud detection and behavioural analytics
- Work as part of an agile cross-functional development team with a “win together, lose together” mindset, having end-to-end responsibility from design and development to deployment, monitoring, and maintenance in production.
- Engineer and select features from large, complex datasets to improve model accuracy and robustness.
- Monitor and evaluate ML models in production, conduct model experiments, comparing variants and identifying improvement and retraining needs.
- Ensure data and model quality, integrity, and reproducibility in production environments.
- Share your knowledge, evolve best practices with your colleagues to boost machine learning at Kleinanzeigen strengthening our ML community.
- Proactively identify opportunities to apply ML for fraud detection and increased user trust.
- Promote ethical AI use, ensuring fairness, transparency, and accountability in all models developed.
- Proactive collaboration with data and application engineers to shape data models and ensure ML-readiness for production.
Qualifications
- Master’s degree in computer science, data science, statistics, mathematics or related field (or equivalent experience)
At least 5+ years of proven experience applying ML methods to build and deploy production-grade models (e.g., XGBoost, Random Forests, Logistic Regression, Neural Networks, Transformers)
Strong proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, XGBoost), with proven experience applying classical ML to structured and time series data, including feature engineering, model evaluation (e.g., precision/recall, AUC), and deploying scalable models (e.g., XGBoost, Random Forests, Logistic Regression) to production.
Solid understanding of ML/DS best practices, including model validation, A/B testing, feature engineering, and pipeline management ensuring quality and robustness of data science outputs.
Practical experience with Large Language Models (LLMs) for tasks such as classification, summarization, or risk signal extraction from unstructured text, with a clear understanding of evaluation and ethical considerations in production use.
True team player mentality, with excellent communication skills including ability to explain complex ML results to non-technical stakeholders.
Preferred qualifications
- Knowledge and experience with fraud detection or Trust & Safety domain
- Familiarity with cloud-based environments (e.g., AWS) and production ML tools (e.g., SageMaker, Airflow, MLflow).
- Experience working in Agile teams with modern DevOps/dataops practices.
- Awareness of ethical and regulatory concerns in AI systems.
Benefits
Life at Adevinta comes with its perks! Our Adevintans enjoy the following benefits:
- An attractive Base Salary
- Participation in our Short-Term Incentive plan (annual bonus)
- Work From Anywhere: Enjoy up to 20 days a year of working from anywhere! Maybe not from the moon well why not! just make sure you have internet connection!
- A 24/7 Employee Assistance Program for you and your family, because we care ❤️
- Win together, lose together is one of our key behaviours. At Adevinta you will find a collaborative environment with an opportunity to explore your potential and grow
On top of these, we also provide a range of locally relevant benefits. Wanna know more? Apply and ask our recruiters! ✨
Adevinta is an equal opportunity employer and we value diversity. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status.
If you feel like you don’t meet all of the requirements for this role but are interested, please consider applying anyway. Research suggests that women and individuals from underrepresented groups may self-select out of opportunities if they don’t meet 100% of the job requirements. We strongly encourage people from historically excluded groups to apply and look forward to speaking with you.