Data Scientist/ML Engineer

Your profile You have a background in data science, AI, statistics, or a related field

You have at least 3 years of experience building data science or machine learning solutions

You are comfortable working in Python

You have experience with modern data/ML tooling (e.g. Docker, Databricks, MLflow, or similar MLOps platforms)

You are interested in media, video, or multimodal content (text, images, video)

You are curious and enjoy exploring new ideas

You enjoy working with others, but are also comfortable working independently

You like taking ownership and driving your own projects

You like working directly with stakeholders and understanding their needs

You enjoy helping others and contributing to a positive team culture

You are comfortable speaking up, sharing your ideas, and staying open to input from others

You are based in the Netherlands and allowed to work here

Your tasks Work on a wide range of problems across the company (e.g. subtitles, forecasting, marketing mix, thumbnails, churn)

Identify and prioritize opportunities for data science, shape them into projects, and drive them forward with stakeholders

Work with stakeholders to understand problems and turn them into data science solutions

Analyze data, build models, create prototypes, experiment with new approaches

Put models into production and keep them running over time

Take ownership of projects from idea to real impact

Work closely with teammates (typically in pairs), support interns, and collaborate with researchers

Bring energy to the team and those around us: share ideas, help others, and contribute to a positive team environment

Your team We are a team of 7 data scientists and a data science manager, looking for one more colleague. We build data products that have a direct impact on our consumers, advertisers, and employees. We work on a wide range of problems. One day, you might build a model to select the most appealing thumbnail for Videoland. Another day, you might help decide what movie to show on RTL 7. The next, you might be fixing a production issue in our search system. No day is the same. The Data Science team is part of the Data Unit, where we work closely with data engineers, analysts, and other specialists. Our tech stack is centered around Python (Pandas, PyTorch, Transformers) and Azure. We work with tools like PySpark, Airflow, MLflow, and Databricks, and deploy our solutions using Docker and Kubernetes. Most of our data comes from Snowflake and Azure Event Hub.

The interview process Our interview process is designed to give you a good sense of the team, the work, and how we collaborate. It also helps us understand how you think and approach problems.

This is what a typical process looks like (we may adapt it along the way if needed): Intro call (1h): get to know each other and learn more about the team Experience interview (1h): discuss your past work and how you approach problems Technical exercise (1h): work on a real data science problem and walk us through your thinking We’re mainly interested in how you think, communicate, and collaborate — not in perfect answers. You should also use these conversations to decide if this is a team you’d enjoy working in.