XING provides advice and support to its more than 14 million members during the upheaval processes in the world of work. In an environment marked by a shortage of skilled workers, digitalization, and changes in values, XING helps its members achieve as harmonious a work/life balance as possible: For a better working life.
Our Data Science team is responsible for turning data into services and products for XING. Around 25 Data scientists, architects and engineers work together to create highly scalable solutions that serve millions of users. We bring state-of-the-art algorithms into production by making use of technologies such as Hadoop (e.g. Hive, Spark), Akka, Kafka, Cassandra, elasticsearch, etc. Learn more about our team at: https://bit.ly/data-science-team
At the moment, we are working intensively on projects related to building advanced ranking models for our search and recommender systems and automating machine learning. Therefore, we are seeking a Data Scientist who helps with designing algorithms/models and implementing these algorithms/models into production services. If you want to get things done rather than sit in meetings, like helping others and learning from them, you will have fun in our team!
A challenging Task
- Solve challenging problems in the context of search, recommender systems and machine learning
- Perform analyses on massive amounts of data and build scalable machine learning models, ranking algorithms and help automating machine learning processes
- Develop new and enhance algorithms and services using technologies such as Scala, elasticsearch, and Hadoop technologies (e.g. Hive, MapReduce)
A convincing Background
- MSc or PhD in Computer Science, Math or similar discipline
- Hands-on experience in exploring large datasets (e.g. with Hive, R, Python, etc.) and creating machine learning models
- Solid programming skills (preferably also in Scala/Java)
- Experience in implementing scalable models and algorithms that process large datasets and are used in production services
- Theoretical and practical knowledge in the information retrieval or machine learning domain (ideally, experience in developing ranking models)
- Proficient English language skills (German is not required)