WHO WE ARE
Schibsted Media Group is an international media group with around 5500 employees in 31 countries. From Mexico to Malaysia, from Brazil to Norway - millions of people interact with Schibsted companies every day. We ensure that new and old sofas can be sold through our digital marketplaces such as Blocket.se, Finn.no, and Leboncoin.fr. News reports are read and watched when, where and how consumers want through Aftonbladet, SvD, VG and Aftenposten. Carpenters are found through a couple of clicks. Prices are compared and the latest fashion is browsed. These examples are just some of the ways our services empower people all around the world in their daily lives.
The mission of our team is to empower Schibsted to leverage AI and Machine Learning for creating smart and data-driven products and services. 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 personalisation. We are now looking for an experienced Data Scientist with experience in building machine learning systems that bring real value.
Check how Schibsted uses Machine Learning to recommend content hereWhat you will do
Who you are
- Apply machine learning and statistics to analyze and solve real-world problems.
- Engineer and implement highly scalable and reliable systems, using the best development practices and tools.
- Work closely with backend engineers in our team to build and productionize ML models that power our services.
- Work closely with other teams (Data Science, Product and UX) at Schibsted to drive product development.
- Engage with internal stakeholders and end-users to better understand their needs, in addition to explain, educate and support them in ML matters.
- Learn a lot and share your own knowledge. Travel occasionally, either to meet colleagues and work together or to attend conferences.
IT'S GREAT IF YOU HAVE
- At least a Master's degree in Computer Science, Software Engineering, Applied Mathematics or any quantitative field.
- Experience of building systems for model training and serving using, e.g., TensorFlow, Keras, or PyTorch
- Understanding and genuine interest of AI and machine learning methods and algorithms, e.g., gradient-based optimization and neural networks
- Experience with development in programming languages such as Python and Java
- Proven track record of shipping technology while dealing with ambiguity, managing cross-team dependencies and relationships
- Experience with cloud providers such as Amazon Web Services or Google Cloud, and being familiar with container-based architectures and microservices
- Experience with distributed computing technologies like Spark, Hadoop, Kafka