Informação sobre: Data Scientist Trainee em Madrid

Empresa que procura Data Scientist Trainee

Madrid, Espanha

Descrição da oferta

The mission is to drive the ML&AI technologies to transform Ericsson to innovate and to enable emerging business. Machine Learning and Artificial Intelligence vision is to utilize and evolve capabilities to drive intelligence and automation in the Edge and in whatever type of solution as a service, to empower our customer´s digital end to end efficiency and to enable intelligence network operations and enterprise solutions. The complexity of today’s networks is massive and will increase further with the introduction of 5G and IoT. Artificial Intelligence and Machine Learning domain is a vital technology for Ericsson to handle this complexity going forward and will be the way for Ericsson to break this growing complexity curve. In this situation, an AI/ML solution, with algorithms which can adapt themselves to the complex environment and the constant changes in user and traffic behaviour, will outperform any human driven solution.  Come and discover what makes YOU + ERICSSON a powerful combination. Now we are looking for an Intern as Data Scientist/Analytics for an internship of 12 months.  As an Intern, you will participate in the development of our NDO portfolio service, based in ML&AI. You will be part of a key Ericsson program, pioneer on the evolution of our current services to the new technologies ML&AI. You will be part of our team of experts with domain and analytics high competences, where you can also participate in the new services definition based in 5G, IoT, … all latest technologies.  What are you going to learn: Develop new use cases to grow our service portfolioAdapt of AI use cases to local requirementsData pipeline to development scenarioCustomer engagements – convert requirement to use casesAutomate process, WoW etc.Lead & support initial Proof of Concepts/Trials 

Descrição do candidato

What competencies we are looking for: Student or Recent Graduate in Engineering: Computer Science, IT, Electrical Engineer or Telecom and MathematicsGood understanding of Machine Learning conceptsVery good analytics skillsGood knowledge of ML libraries, such as Keras, H2O, scikit, Tensorflow, etc.Very good programming skillsGood understanding of various Data Learning architectures & concepts (ANN, CNN, LSTM, GAN, etc.) as well as hyperparameter optimizationGood understanding of analytics and unsupervised learning concepts (network graph theory, community detection, clustering algorithms)English knowledge is mandatory