You may not recognise our name, but Schibsted Media Group technologies and companies empower people every day, in every corner of the world through our media and marketplace products. Schibsted employs 6,800 people across 30 countries worldwide, all dedicated to helping our 200 million users discover, build and connect. Our customers use us to sell new and old sofas, keep up with current affairs, check the weather, find a carpenter, compare prices, follow the latest fashions…and so much more!
Scientists and engineers in our Data team are working alongside on the next generation of data products that are at the heart of Schibsted’s strategy for accelerating user growth and providing users with relevant, personalized content. We offer one of the largest and most diverse data sets in the world and we work with the latest data technologies (Spark, AWS services, Cassandra, Kafka). At the same time, we also believe that our scientists and engineers are at their best when they share ideas, problems, and solutions with each other, and so we are joined together as a unified data science team. While we work in different application areas, we support one another and push each other to constantly learn and perfect our craft. Our ambition is nothing short of becoming one of the leading sources of innovation in applied machine learning and artificial intelligence in the world.
As a Data Scientist within the Search and Discovery team, you will work alongside a group of highly talented scientists and engineers based in Barcelona and London, providing the fundamental science powering search and recommendations across our online media and marketplace products.
- Apply expertise in quantitative analysis, machine learning, and data mining to a variety of product areas including personalized recommendations, classifiers, user growth, and A/B experimentation.
- Partner closely with product teams to deliver insights and recommendations that inform product direction and strategy.
- Communicate findings and results to both technical and non-technical audiences.
- Assess the value of new data sources and help drive the collection of new data.
- Design and interpret the results of product experiments.
- PhD or Masters degree (or equivalent) in a relevant technical field such as computer science, statistics, or operations research.
- Extensive experience applying quantitative approaches to practical problems.
- Comfort with relational databases and SQL. Experience with at least one scripting language such as Python (preferred), Ruby, or Perl.
- Experience with statistical programming environments like R or Python/Pandas.
- Experience with Scala is a plus.
- Experience with large data sets, distributed computing, and MapReduce a plus.