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DESCRIPTION OF THE TASKS Development, maintenance and documentation software, mostly in python, with a focus on implementing and testing data analytics applications, data engineering and data collection tools.
Participate in data science projects led by ECAT scientific staff, and assume responsibility for software engineering tasks, including among others, requirement analysis, software development testing and documentation.
Participation in project update and review meetings and other meetings with project stakeholders.
KNOWLEDGE AND SKILLS Excellent software development skills, in particular, experience implementing python libraries, software and services.
Demonstrated experience in implementing best practices for software testing, from unit and component testing to user acceptance, including negative testing and stress tests, to ensure software quality and reliability.
Experience deploying software tools and services, including definition of APIs, using DevOps tools and practices, CI/CD practices, e.g. in Gitlab or similar environments.
Experience in debugging complex software in python, and troubleshooting aspects related to the deployment of software, such as setting up execution environments, resolving dependencies, installing drivers, analysing networking aspects and using GPU hardware.
Experience in containerization and orchestration technologies such as Docker, Kubernetes or equivalent for the deployment and scaling of data science applications.
Ability and willingness to stay up to date with technologies and libraries for machine learning and data science.
Ability to write clear technical documentation of software for users and other developers, in English language.
Ability to design and implement robust data pipelines for the ingestion, cleaning, transformation and storage of diverse data sources.
Strong experience in testing software, including frameworks for defining and automating software tests, including regression testing and negative testing
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