Senior Data Engineer - Machine Learning Team

We are currently looking for a talented Data Engineer to join our Machine Learning Team in Stockholm. The mission of our team is to empower Schibsted to leverage AI and Machine Learning for creating smart and data-driven products and services for all the Schibsted brands. We collaborate closely with product and engineering teams to build models and services that add value in terms of, e.g., increased relevance, automation, and personalization.

Here are some examples of ongoing or planned machine learning work in Schibsted:

- Personalization and moderation of media content
- Image processing and classification
- Content recommendation & classification using Natural Language Processing (NLP)

In this role you will:

- Contribute to designing, building, training, evaluating, shipping, and refining ML-driven products
- Collaborate closely with a cross-functional agile team spanning data science, product management, and engineering to build prototypes as well as production-ready solutions
- Consider engineering as a whole by making the pragmatic tradeoffs in terms of security, performance, maintainability, availability, and cost
- Coordinate work across team boundaries
- Foster a culture of mentorship and knowledge sharing within the team

Who you are:

- You have experience with programming languages such as Python and Scala
- You are comfortable explaining the intuition and assumptions behind ML concepts
- You have experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
- You preferably have experience with and cloud platforms like GCP or AWS.
- You have strong communication skills
- We are looking for a candidate with 4+ years of experience in a Data Engineer role




Schibsted Data & Tech is a central product and tech unit that serves all of Schibsted. We are about 250+ people in Oslo, Stockholm and Krakow, and collaborate closely with other product and tech teams in all units in Schibsted. Areas of responsibilities include data & technology strategy, privacy/data trends/responsible data & machine learning, information security and internal IT.