Data Scientist | Onsite

Engineering International Belgium; Ispra; On-site; EUR 52,000 - 70,000; Full time

Job summary

Engineering International Belgium is seeking a software engineer to develop and maintain Python-based data analytics tools and data pipelines. You will contribute to data science projects, handle requirements analysis, testing and documentation, and participate in stakeholder meetings to align on progress and deliverables.

The role emphasizes strong software testing, DevOps practices, and English-language technical documentation. Experience with Docker/Kubernetes and data pipelines is a plus.

Qualifications

• Experience implementing Python libraries, software and services.
• Experience applying best practices for software testing (unit, component, UI/acceptance, negative, stress).
• Experience deploying tools/services with DevOps practices and CI/CD (GitLab or similar).
• Experience debugging complex Python software and deployment issues (environments, dependencies, drivers, networking).
• Experience in containerization/orchestration (Docker, Kubernetes) for deployment/scaling of data science apps.
• Ability to stay up to date with ML/data science libraries and technologies.
• Ability to write clear technical docs in English for users and developers.
• Ability to design robust data pipelines for ingestion, cleaning, transformation and storage of diverse data sources.
• Strong testing experience with regression and negative testing frameworks.

Responsibilities

• Develop, maintain and document Python software for data analytics and data collection tools.
• Contribute to data science projects, covering requirements analysis, development testing and documentation.
• Participate in project update and stakeholder meetings.

Skills

Python programming

Software testing

DevOps practices

CI/CD

APIs definition

Tools

Docker

Kubernetes

Job description

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