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This role focuses on developing data-driven solutions for a European Institution, ensuring compliance with regulatory frameworks and enhancing data processes. You will work remotely within a multicultural environment, contributing to the institution's mission of effective data management and policy implementation.
NRB
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Joining KEYES means giving purpose to your talent.
Are you looking for an environment where technology is not an end in itself, but a lever to build a sustainable future? At KEYES, we are not just looking for technical expertise; we are looking for people who share our values.
Do you want to continue your career and grow within one of Belgium’s leading IT companies?
Join KEYES as a Data Scientist!
KEYES is a dynamic global organization that takes pride in being the trusted partner of EU Institutions. With strong commitment to excellence and a 30-years track record of delivering high-quality solutions, we are dedicated to supporting the growth and success of our clients. Our Mission is to help our clients keep up with the challenges of digital transformation by providing the right talent at the right time for the right job. To this end, we are constantly looking for talented professionals who are interested in working on challenging international projects and able to deliver high-quality results within multicultural environments. Our services include (but are not limited to) Modernization of Solutions, Digital Workspaces, Infrastructure & Cloud Solutions, Cybersecurity Solutions, Business Software Solutions, Mainframe Solutions, Data & AI Solutions, Advisory Solutions, and Staffing Solutions. Our Headquarters are in Brussels and we have active accounts and offices across Europe (i.e. Luxembourg, Athens, Brussels, etc.)
More information: www.keyes.eu
THE BACKGROUND
For our client, a European Institution based in Brussels, we are looking for an experienced Data Scientistto join remotely for a long-term mission.
More specifically, you will be responsible for…
Developing and implementing machine learning algorithms, statistical models, and scripts to solve specific business problems.
Conducting rigorous experiment design (e.g., A/B testing), employing cross-validation techniques, and performing statistical significance testing to validate findings and model performance.
Elaborating processes to ensure the compliant implementation of regulatory frameworks (e.g., EU AI Act), including model risk management, monitoring for drift/bias, and comprehensive documentation (e.g., model cards).
Data collection, transformation and integration: Analysing the needs and identify suitable data sources and flows. Organising the execution of the data collection and integration processes, verifying results, proposing improvements and implementing them in cooperation with the IT department. Organising the related user acceptance tests. This task will generate up-to-date data collection, transformation and integration processes and tools, updated databases with integrated data, up-to-date analysis documents, process documentation and reports.
Data validation, visualisation and publication: Organising the data validation and the data quality checks, including through automated processes. Analyzing needs and creating reports, data visualisations and publications, in cooperation with the IT department. Organising the related user acceptance tests. This sub-task will generate up-to-date data validation processes, updated databases with validated data, up-to-date process documentation and reports, up-to-date reports, data visualisations and publications.
Supporting data providers in the communication of data through the creation of templates, tools and guidance documents. Supporting both data providers and users at various stages of the data validation processes. Organising the support to users asking for access, clarification or information on data. This task will generate templates, tools, guidance documents and managed data helpdesk tickets.
Data policies: Collaborating in assessing the implementation of DG AGRI data policies and ensure data policies are implemented for new data collections.
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