At CGD (Permanent), in Lisbon, Portugal
Expires at: ********
Remote policy: Onsite job
Caixa Geral de Depósitos (CGD) is a major player in the Portuguese financial market. CGD, formed as a public limited liability company by the Portuguese state, in 1876, is one of Portugal's leading institutions and is fully owned by the Republic of Portugal.
CGD has been at the forefront of Portuguese economic and social development. Based on a strong corporate culture and the highest ethical standards, rigour and professionalism, CGD has received over the years various awards and is recognized as a highly reliable, solid bank in Portugal's banking sector, having merited the confidence of its many generations of customers.
Caixa's strategy for action involves effectiveness and innovation, in services to families and companies, as a partner in growth and sustained development. Caixa is socially responsible, looking out for everyone's interests, including those of future generations, respecting basic principles such as respect for human rights, environmental conservation and social progress of the community it is involved in.
CGD is looking for a Data Scientist Trainee to join their team in Lisbon. Main requirements Degree in mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience; Experience performing Data Science projects (less than one year); Experience on performing full lifecycle of machine learning model development activities (including data engineering): ETL, pipelines, data models; Feature engineer, validation and assessment; Activities post-production like including monitoring, re-training, re-engineering, as well model management; Demonstrated statistical knowledge; Strong knowledge of Python programming language and/or R/Scala; Experience working with large scale unstructured and structured datasets and databases; Experience with Big Data Frameworks (HIVE, HDFS, Spark); Experience applying advanced analytics solutions to solve complex business problems; Experience on data science tools like MLFlow, Kubeflow, H20 or similar; Experience using supervised, unsupervised and semi supervised techniques on large, disparate and unbalanced datasets. Nice to have Experience on communicating findings to other Data Scientists and Business Managers; Strong team spirit, leadership capability, dynamism and communication capacity; Preferable experience in bank or finance sectors; Ability to work at a tactical and strategic level simultaneously.
